{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Copyright 2021 NVIDIA Corporation. All Rights Reserved.\n",
    "#\n",
    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#\n",
    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
    "#\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TF-TRT Dynamic shapes example: UNet\n",
    "\n",
    "The goal of this notebook is to demonstrate TF-TRT support for converting a network that has dynamic image size. While earlier TRT versions allowed only the batch size to be unknown, with dynamic shape mode other dimensions can be dynamic.\n",
    "\n",
    "We take a fully convolutional network, UNet as an example.\n",
    "The network and many of the code samples in this notebook are from https://keras.io/examples/vision/oxford_pets_image_segmentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Requirements\n",
    "This notebook requires at least TF 2.5 and TRT 7.1.3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"TF_CPP_VMODULE\"]=\"trt_engine_utils=2,segment=2\" # verbose output\n",
    "os.environ[\"TF_TRT_OP_DENYLIST\"] = \"Shape\"                  # workaround for shape output memory error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pillow in /usr/local/lib/python3.8/dist-packages (8.1.2)\n",
      "Requirement already satisfied: matplotlib in /usr/local/lib/python3.8/dist-packages (3.4.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (2.8.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (0.10.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (2.4.7)\n",
      "Requirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (1.19.4)\n",
      "Requirement already satisfied: six in /usr/local/lib/python3.8/dist-packages (from cycler>=0.10->matplotlib) (1.15.0)\n",
      "\u001b[33mWARNING: You are using pip version 21.0; however, version 21.0.1 is available.\n",
      "You should consider upgrading via the '/usr/bin/python -m pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install pillow matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Enabling eager execution\n",
      "INFO:tensorflow:Enabling v2 tensorshape\n",
      "INFO:tensorflow:Enabling resource variables\n",
      "INFO:tensorflow:Enabling tensor equality\n",
      "INFO:tensorflow:Enabling control flow v2\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.python.compiler.tensorrt import trt_convert as trt\n",
    "import numpy as np\n",
    "from tensorflow.python.saved_model import signature_constants\n",
    "from tensorflow.python.saved_model import tag_constants\n",
    "from tensorflow.python.framework import convert_to_constants\n",
    "import time\n",
    "\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers\n",
    "from tensorflow.keras.preprocessing.image import load_img\n",
    "\n",
    "from IPython.display import Image, display\n",
    "from tensorflow.keras.preprocessing.image import load_img\n",
    "import PIL\n",
    "from PIL import ImageOps\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, None, None,  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d (Conv2D)                 (None, None, None, 3 896         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization (BatchNorma (None, None, None, 3 128         conv2d[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "activation (Activation)         (None, None, None, 3 0           batch_normalization[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, None, None, 3 0           activation[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d (SeparableConv (None, None, None, 6 2400        activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, None, None, 6 256         separable_conv2d[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, None, None, 6 0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d_1 (SeparableCo (None, None, None, 6 4736        activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, None, None, 6 256         separable_conv2d_1[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D)    (None, None, None, 6 0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, None, None, 6 2112        activation[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add (Add)                       (None, None, None, 6 0           max_pooling2d[0][0]              \n",
      "                                                                 conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, None, None, 6 0           add[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d_2 (SeparableCo (None, None, None, 1 8896        activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, None, None, 1 512         separable_conv2d_2[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, None, None, 1 0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d_3 (SeparableCo (None, None, None, 1 17664       activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, None, None, 1 512         separable_conv2d_3[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, None, None, 1 0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, None, None, 1 8320        add[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, None, None, 1 0           max_pooling2d_1[0][0]            \n",
      "                                                                 conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, None, None, 1 0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d_4 (SeparableCo (None, None, None, 2 34176       activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, None, None, 2 1024        separable_conv2d_4[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, None, None, 2 0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "separable_conv2d_5 (SeparableCo (None, None, None, 2 68096       activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, None, None, 2 1024        separable_conv2d_5[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, None, None, 2 0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, None, None, 2 33024       add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, None, None, 2 0           max_pooling2d_2[0][0]            \n",
      "                                                                 conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, None, None, 2 0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose (Conv2DTranspo (None, None, None, 2 590080      activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, None, None, 2 1024        conv2d_transpose[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, None, None, 2 0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_1 (Conv2DTrans (None, None, None, 2 590080      activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, None, None, 2 1024        conv2d_transpose_1[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_1 (UpSampling2D)  (None, None, None, 2 0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d (UpSampling2D)    (None, None, None, 2 0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, None, None, 2 65792       up_sampling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, None, None, 2 0           up_sampling2d[0][0]              \n",
      "                                                                 conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, None, None, 2 0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_2 (Conv2DTrans (None, None, None, 1 295040      activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, None, None, 1 512         conv2d_transpose_2[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, None, None, 1 0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_3 (Conv2DTrans (None, None, None, 1 147584      activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, None, None, 1 512         conv2d_transpose_3[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_3 (UpSampling2D)  (None, None, None, 2 0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_2 (UpSampling2D)  (None, None, None, 1 0           batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, None, None, 1 32896       up_sampling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, None, None, 1 0           up_sampling2d_2[0][0]            \n",
      "                                                                 conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, None, None, 1 0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_4 (Conv2DTrans (None, None, None, 6 73792       activation_11[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, None, None, 6 256         conv2d_transpose_4[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, None, None, 6 0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_5 (Conv2DTrans (None, None, None, 6 36928       activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, None, None, 6 256         conv2d_transpose_5[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_5 (UpSampling2D)  (None, None, None, 1 0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_4 (UpSampling2D)  (None, None, None, 6 0           batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, None, None, 6 8256        up_sampling2d_5[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, None, None, 6 0           up_sampling2d_4[0][0]            \n",
      "                                                                 conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, None, None, 6 0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_6 (Conv2DTrans (None, None, None, 3 18464       activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, None, None, 3 128         conv2d_transpose_6[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, None, None, 3 0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_7 (Conv2DTrans (None, None, None, 3 9248        activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, None, None, 3 128         conv2d_transpose_7[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_7 (UpSampling2D)  (None, None, None, 6 0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "up_sampling2d_6 (UpSampling2D)  (None, None, None, 3 0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, None, None, 3 2080        up_sampling2d_7[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, None, None, 3 0           up_sampling2d_6[0][0]            \n",
      "                                                                 conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, None, None, 3 867         add_6[0][0]                      \n",
      "==================================================================================================\n",
      "Total params: 2,058,979\n",
      "Trainable params: 2,055,203\n",
      "Non-trainable params: 3,776\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "def get_model(img_size, num_classes):\n",
    "    inputs = keras.Input(shape=img_size + (3,))\n",
    "\n",
    "    ### [First half of the network: downsampling inputs] ###\n",
    "\n",
    "    # Entry block\n",
    "    x = layers.Conv2D(32, 3, strides=2, padding=\"same\")(inputs)\n",
    "    x = layers.BatchNormalization()(x)\n",
    "    x = layers.Activation(\"relu\")(x)\n",
    "\n",
    "    previous_block_activation = x  # Set aside residual\n",
    "\n",
    "    # Blocks 1, 2, 3 are identical apart from the feature depth.\n",
    "    for filters in [64, 128, 256]: #[16, 32, 64]:\n",
    "        x = layers.Activation(\"relu\")(x)\n",
    "        x = layers.SeparableConv2D(filters, 3, padding=\"same\")(x)\n",
    "        x = layers.BatchNormalization()(x)\n",
    "\n",
    "        x = layers.Activation(\"relu\")(x)\n",
    "        x = layers.SeparableConv2D(filters, 3, padding=\"same\")(x)\n",
    "        x = layers.BatchNormalization()(x)\n",
    "\n",
    "        x = layers.MaxPooling2D(3, strides=2, padding=\"same\")(x)\n",
    "\n",
    "        # Project residual\n",
    "        residual = layers.Conv2D(filters, 1, strides=2, padding=\"same\")(\n",
    "            previous_block_activation\n",
    "        )\n",
    "        x = layers.add([x, residual])  # Add back residual\n",
    "        previous_block_activation = x  # Set aside next residual\n",
    "\n",
    "    ### [Second half of the network: upsampling inputs] ###\n",
    "\n",
    "    for filters in [256, 128, 64, 32]: #[64, 32, 16, 8]:\n",
    "        x = layers.Activation(\"relu\")(x)\n",
    "        x = layers.Conv2DTranspose(filters, 3, padding=\"same\")(x)\n",
    "        x = layers.BatchNormalization()(x)\n",
    "\n",
    "        x = layers.Activation(\"relu\")(x)\n",
    "        x = layers.Conv2DTranspose(filters, 3, padding=\"same\")(x)\n",
    "        x = layers.BatchNormalization()(x)\n",
    "\n",
    "        x = layers.UpSampling2D(2)(x)\n",
    "\n",
    "        # Project residual\n",
    "        residual = layers.UpSampling2D(2)(previous_block_activation)\n",
    "        residual = layers.Conv2D(filters, 1, padding=\"same\")(residual)\n",
    "        x = layers.add([x, residual])  # Add back residual\n",
    "        previous_block_activation = x  # Set aside next residual\n",
    "\n",
    "    # Add a per-pixel classification layer\n",
    "    outputs = layers.Conv2D(num_classes, 3, activation=\"softmax\", padding=\"same\")(x)\n",
    "\n",
    "    # Define the model\n",
    "    model = keras.Model(inputs, outputs)\n",
    "    return model\n",
    "\n",
    "\n",
    "# Free up RAM in case the model definition cells were run multiple times\n",
    "keras.backend.clear_session()\n",
    "\n",
    "# Build model with uknwown image size\n",
    "img_size = (None, None)\n",
    "\n",
    "num_classes = 3\n",
    "model = get_model(img_size, num_classes)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare data\n",
    "Instructions to download can be found in the [link above](https://keras.io/examples/vision/oxford_pets_image_segmentation)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define input paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of samples: 7390\n",
      "unet_pets/images/Abyssinian_1.jpg | unet_pets/annotations/trimaps/Abyssinian_1.png\n",
      "unet_pets/images/Abyssinian_10.jpg | unet_pets/annotations/trimaps/Abyssinian_10.png\n",
      "unet_pets/images/Abyssinian_100.jpg | unet_pets/annotations/trimaps/Abyssinian_100.png\n",
      "unet_pets/images/Abyssinian_101.jpg | unet_pets/annotations/trimaps/Abyssinian_101.png\n",
      "unet_pets/images/Abyssinian_102.jpg | unet_pets/annotations/trimaps/Abyssinian_102.png\n",
      "unet_pets/images/Abyssinian_103.jpg | unet_pets/annotations/trimaps/Abyssinian_103.png\n",
      "unet_pets/images/Abyssinian_104.jpg | unet_pets/annotations/trimaps/Abyssinian_104.png\n",
      "unet_pets/images/Abyssinian_105.jpg | unet_pets/annotations/trimaps/Abyssinian_105.png\n",
      "unet_pets/images/Abyssinian_106.jpg | unet_pets/annotations/trimaps/Abyssinian_106.png\n",
      "unet_pets/images/Abyssinian_107.jpg | unet_pets/annotations/trimaps/Abyssinian_107.png\n"
     ]
    }
   ],
   "source": [
    "input_dir = \"unet_pets/images/\"\n",
    "target_dir = \"unet_pets/annotations/trimaps/\"\n",
    "\n",
    "input_img_paths = sorted(\n",
    "    [\n",
    "        os.path.join(input_dir, fname)\n",
    "        for fname in os.listdir(input_dir)\n",
    "        if fname.endswith(\".jpg\")\n",
    "    ]\n",
    ")\n",
    "target_img_paths = sorted(\n",
    "    [\n",
    "        os.path.join(target_dir, fname)\n",
    "        for fname in os.listdir(target_dir)\n",
    "        if fname.endswith(\".png\") and not fname.startswith(\".\")\n",
    "    ]\n",
    ")\n",
    "\n",
    "print(\"Number of samples:\", len(input_img_paths))\n",
    "\n",
    "# Just print a few image paths\n",
    "for input_path, target_path in zip(input_img_paths[:10], target_img_paths[:10]):\n",
    "    print(input_path, \"|\", target_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Helper class to load the images and convert to a fixed size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class OxfordPets(keras.utils.Sequence):\n",
    "    \"\"\"Helper to iterate over the data (as Numpy arrays).\"\"\"\n",
    "\n",
    "    def __init__(self, batch_size, img_size, input_img_paths, target_img_paths):\n",
    "        self.batch_size = batch_size\n",
    "        self.img_size = img_size\n",
    "        self.input_img_paths = input_img_paths\n",
    "        self.target_img_paths = target_img_paths\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.target_img_paths) // self.batch_size\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        \"\"\"Returns tuple (input, target) correspond to batch #idx.\"\"\"\n",
    "        i = idx * self.batch_size\n",
    "        batch_input_img_paths = self.input_img_paths[i : i + self.batch_size]\n",
    "        batch_target_img_paths = self.target_img_paths[i : i + self.batch_size]\n",
    "        x = np.zeros((self.batch_size,) + self.img_size + (3,), dtype=\"float32\")\n",
    "        for j, path in enumerate(batch_input_img_paths):\n",
    "            img = load_img(path, target_size=self.img_size)\n",
    "            x[j] = img\n",
    "        y = np.zeros((self.batch_size,) + self.img_size + (1,), dtype=\"uint8\")\n",
    "        for j, path in enumerate(batch_target_img_paths):\n",
    "            img = load_img(path, target_size=self.img_size, color_mode=\"grayscale\")\n",
    "            y[j] = np.expand_dims(img, 2)\n",
    "            # Ground truth labels are 1, 2, 3. Subtract one to make them 0, 1, 2:\n",
    "            y[j] -= 1\n",
    "        return x, y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define train and test sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "\n",
    "def train_test_split(input_img_paths, target_img_paths):\n",
    "    # Split our img paths into a training and a validation set\n",
    "    val_samples = 1000\n",
    "    random.Random(1337).shuffle(input_img_paths)\n",
    "    random.Random(1337).shuffle(target_img_paths)\n",
    "    train_input_img_paths = input_img_paths[:-val_samples]\n",
    "    train_target_img_paths = target_img_paths[:-val_samples]\n",
    "    val_input_img_paths = input_img_paths[-val_samples:]\n",
    "    val_target_img_paths = target_img_paths[-val_samples:]\n",
    "    return train_input_img_paths, train_target_img_paths, val_input_img_paths, val_target_img_paths\n",
    "\n",
    "train_inp_paths, train_target_paths, val_inp_paths, val_target_paths = \\\n",
    "    train_test_split(input_img_paths, target_img_paths)\n",
    "\n",
    "# Instantiate data Sequences for each split\n",
    "img_size = (160, 160)\n",
    "batch_size = 4\n",
    "train_gen = OxfordPets(batch_size, img_size, train_inp_paths, train_target_paths)\n",
    "val_gen = OxfordPets(batch_size, img_size, val_inp_paths, val_target_paths)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n",
      "1597/1597 [==============================] - 56s 31ms/step - loss: 0.9462 - val_loss: 0.4681\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/generic_utils.py:494: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
      "  warnings.warn('Custom mask layers require a config and must override '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/15\n",
      "1597/1597 [==============================] - 48s 30ms/step - loss: 0.4586 - val_loss: 0.4917\n",
      "Epoch 3/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.3975 - val_loss: 0.4584\n",
      "Epoch 4/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.3509 - val_loss: 0.3846\n",
      "Epoch 5/15\n",
      "1597/1597 [==============================] - 48s 30ms/step - loss: 0.3237 - val_loss: 0.3682\n",
      "Epoch 6/15\n",
      "1597/1597 [==============================] - 48s 30ms/step - loss: 0.2979 - val_loss: 0.3473\n",
      "Epoch 7/15\n",
      "1597/1597 [==============================] - 47s 30ms/step - loss: 0.2768 - val_loss: 0.3746\n",
      "Epoch 8/15\n",
      "1597/1597 [==============================] - 48s 30ms/step - loss: 0.2581 - val_loss: 0.3554\n",
      "Epoch 9/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.2429 - val_loss: 0.3554\n",
      "Epoch 10/15\n",
      "1597/1597 [==============================] - 47s 30ms/step - loss: 0.2274 - val_loss: 0.3767\n",
      "Epoch 11/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.2168 - val_loss: 0.3638\n",
      "Epoch 12/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.2069 - val_loss: 0.3514\n",
      "Epoch 13/15\n",
      "1597/1597 [==============================] - 47s 30ms/step - loss: 0.1986 - val_loss: 0.3756\n",
      "Epoch 14/15\n",
      "1597/1597 [==============================] - 47s 30ms/step - loss: 0.1907 - val_loss: 0.3470\n",
      "Epoch 15/15\n",
      "1597/1597 [==============================] - 47s 29ms/step - loss: 0.1831 - val_loss: 0.3520\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x7faf9dae4dc0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Configure the model for training.\n",
    "# We use the \"sparse\" version of categorical_crossentropy\n",
    "# because our target data is integers.\n",
    "model.compile(optimizer=\"rmsprop\", loss=\"sparse_categorical_crossentropy\")\n",
    "\n",
    "callbacks = [\n",
    "    keras.callbacks.ModelCheckpoint(\"oxford_segmentation.h5\", save_best_only=True)\n",
    "]\n",
    "\n",
    "# Train the model, doing validation at the end of each epoch.\n",
    "epochs = 15\n",
    "model.fit(train_gen, epochs=epochs, validation_data=val_gen, callbacks=callbacks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the trained model in savedmodel format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:FOR KERAS USERS: The object that you are saving contains one or more Keras models or layers. If you are loading the SavedModel with `tf.keras.models.load_model`, continue reading (otherwise, you may ignore the following instructions). Please change your code to save with `tf.keras.models.save_model` or `model.save`, and confirm that the file \"keras.metadata\" exists in the export directory. In the future, Keras will only load the SavedModels that have this file. In other words, `tf.saved_model.save` will no longer write SavedModels that can be recovered as Keras models (this will apply in TF 2.5).\n",
      "\n",
      "FOR DEVS: If you are overwriting _tracking_metadata in your class, this property has been used to save metadata in the SavedModel. The metadta field will be deprecated soon, so please move the metadata to a different file.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/generic_utils.py:494: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.\n",
      "  warnings.warn('Custom mask layers require a config and must override '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: unet_pets_saved_model/assets\n"
     ]
    }
   ],
   "source": [
    "tf.saved_model.save(model, 'unet_pets_saved_model')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_results(x, y, preds):\n",
    "    # x and y has a batch of images, we will visualize the first one\n",
    "    idx = 1\n",
    "    fig = plt.figure(figsize=(16,5))\n",
    "    ax = fig.add_subplot(131)\n",
    "    ax.imshow(x[idx,:,:,:].astype(np.uint8))\n",
    "    ax.set_title('input')\n",
    "    ax = fig.add_subplot(132)\n",
    "    ax.imshow(y[idx,:,:,:])\n",
    "    ax.set_title('ground_truth')\n",
    "    ax = fig.add_subplot(133)\n",
    "    # process the prediction\n",
    "    mask = np.argmax(preds[idx], axis=-1)\n",
    "    mask = np.expand_dims(mask, axis=-1)\n",
    "    img = PIL.ImageOps.autocontrast(keras.preprocessing.image.array_to_img(mask))\n",
    "    #ax.imshow(preds[idx,:,:,:])\n",
    "    ax.imshow(img)\n",
    "    ax.set_title('predictions')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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s8kGfpnPZyZytd53Fcrnj7B/y9INHeLr/BAuqO7X/Ra0HecaXPMRdjxyA48EFsPDyxr7rLBbLueSCJTqqUkjE9K9SeOgku2ephDHFZyHNLarRlf65wmQd34lg1HoiWnIPWKXrmwkxxUSQGRGMZILFgOQCMz8EgylEIyWrppPhqDwTqdTLNlyRQh+ZVHwYSAcn8/3V+pu8cmWxXagdqQXwmqoFUhJwxfVodCVL5T5Nzqt6JfLjKnZhMk9b5gWthW03CXXK11IAbRAzEX/T4rCi7ma47SZZZXORhQFlMps1oKazI0/Vkns+MROvdHF+IE7V67cdj6vJsh3HRuPi4KCKAZTsQSxE4CzP8CSkN78MMxaIkYl3s7pnWlBKPvhjJPuOZG2Y9FtYDCCISn9qthUe/cJbrMGk2ZVF3KL+1NaLR5haLJYzpPSKeMHVj/C/r/srYFqQAjw3CPjjmz7E6+Kv474TV15MY1cWi8WS0tRls+8yYMeI0ieHMPG81DvWFW+lkiIUE1IRoTLxUg+HTfeXvYdlmvxOFB7SioCq2bE9UhGee25TcSqFN7Fe32ahvLmXdtbzXr5Ok2Q/Km23kqipqe2q13A6xHbarrLHrdz2rCQ+acbakj+35K0rua0ngwhMX+uZ3uS6N7XxXk88iVuGz2ZewnT9n9O539XWskWDQAxKgYkionjI0vIyIor19Q2M0Whj8Nz0K9wUxlwmF6STgYTpjM6G7I5uYvpE2BoMSTagoAvvcL3OqfMrffdSh/zk2M0GaSwWy6XJ13/pJ3nNfLrU5VP9Y8wSpGX+0w3v49NXXM3P/M3rUQM7x9RisVwc6IWY//CKP6CjxsW22/o38K6/fnnqYbvM2dGidCoscpMOayEI0wMLkVLsL4mOiliTujbJhVneUZ60nhbIPZLlhkse2Fqn/EzmIqbeQ5NKSSlOZ8oz2SikGz6biRppaKoabjwpVhLq1K5vceLTdtebmU7KVL0v02K0fJ9zT+/0oIEpX4uJWzkT8dOCrMmTKtUbP7GjJHCrtjWc8VRbuVA/vXueh8yWpbEoodVqEztj4rHGc9N5zb7roI1DfdmbRjvLnu/JxhnnVHu2K+dV21h8D1Kvbf2gpkGG8pI9WchD7ZiyDaZR1FoslksD3dY48yFfs3AHX9mJsq1bC1KAZ/st9jsP8jOOfUdYLJaLA70UsXvPOt/YO0ogXrF9r/MZ3rP3+RiT9tfNSR+JL88B+h0tSmF7ndNUn5RDaiciqtw5FlEl55pkyXby9RnLy7GktZrij3LN+U/e+MS31eSha/o88zwqZYqZf0VnPQ1vlIay1eOnl4iZLYyVEpTUkkwpqXh80dPieiIgSueYGjFTmBtdtlFTFyWlWorPxThDvayoKd0nTnYeRjcqq2qCISmS9UwqyHyUxblP1zFT/FXaqO8vZ5adZjKYkofjKjAJbS/gqTfeyHDQZ2N9lfE4xBjYs2sZjYNGcerUMZIkQSnV+F1RIohSmCQhn1PdxGZL7+T7i3OX+veB4nf6ndras1z5jjLxvlpPqcVyeXDjTY/zJ099f6VzZrFYLJckAj/z0j/i2+Yen3rnvaTl8Lkv+3UAVnXISz78T+Hk5fle3PGiFKbFZWOoZ6180+fy39X5lvX9pfoL52sqkMrzVAsP3bR7cEtbyuGrs86VkucybaZZkG52fYpz3EwgNHh0K9elLt6K6mre5xnnU1RYuRbp+pl5Bt1pm+ptVe2luI/lQqV5kTOek6m/G7y/k+PSLU1CtPke0FBm+yP5eXuCwVEKBxj1+4zHIVEiiAoQA7EWlONkgwkKSDKR35z4qhqS3mxPeU5pk831Z8+Qi8+8/tyjv7VXOQ/dnXzPIB8Eqj+7Fovl0sQRbQWpxWK55FH7R7zi+vt5YesRAuk0lsnfhR1Jiki0y5EdKUqbPaObeB3T3mxlv8E0iolKjSLZ3L+JKJvoiCwbqEghSKXw3JVFzXQXvsljWLa7kvV0pnUTT1JW3aZsFsZZzCndRid/EqZMER4qtZOc1F8VpUI5J25NhEPqASz2QZ4cZ8oGUzO1wezilk9U6CTcdvNTnCo/3X62R6Xe2E2X29mC0vjCJmVMMeiQi1IvE6XD9Q3GiSFKBNfxECUkSYIowVGqNF9YZ9e3eXAhHzSYZcZElJpagHWjxeQZeavntrUgzc+XLJFRedBlkl/rTMPeLRbLxYBxDK6yE6gsFsuljXHg5oNP8FtX/x3QLEjriGMwDkhybm3biew4UTpr3cSU5k5qXSjmnrSyd3E6i2i63VHTa4+qfA3Gcv3m9Lxe5TpnhR9XZy5uh9MPbzRbqCIRtXWN2zCzco7bNNEAphTuObFJtuXdq5hYeGS3WbYmSkXSsF2V5l4uEiYVopytQ3dnYYyueBGb6kgT2poifLjb7eK7LnEYkeBgsp/04iqiSBOG41Sc4kxCkk0toZTWFbE+y5t9eomOckG5xcjBDJRSqafVSOopJ5+TOvv6WCyWSwPdTfilV7+TZ/lHgd6FNsdisVjOCbqb8EuvOb13XVt8/uDlb+d9qy/gXX/58nNr4A5EbV3kPLCFjthsyQvJwjYLz2TJiTftMcwbK4VnFh7SyQ+lkFwp2mmKYi17EKe9U7OyoUrJ1qm26xfDZOdnZoWHzr4uxX6pzYaV0vWq1VVsMeQzZWm6imUvKZXrLtV9Ren879SK4pApj9i0bUjZitJ9KX6Eeqvptaq2SUWeyVRdTWe52eeJeXWPYe4BPM0QDGNwFPieg+OkSY1iI1nyJAetIUlAm8l9dBwHRzmTeyXZ3On8rBqvY/m6zDhxqR1LfXAlfSaldPUbv6cT9yeUMy5Xog5Kd1JKFl6+ESwWy6WLY3hZ6xjXeZt30h6MNviHh17ChwZ2PVKLxXIRss13XeUQUTw3CHhm+7HT9UFdEuwMUYpBaz3p9Ob6IcuF0yyOSuS9WJUmdWkUpLkKyvvqyoCkiWAcpVIvWVnkZh1kJYIDuAKOgBKnCJNMm07/Ko6thSmevnctnWepSmGzkomSqfOhLMybUUqlnrAGYWoarpFIej6OmfwoU5xlfqEnQlTl11UQR+GoXCSBoCY/IqRO6YkVogTHcRHlUKxrWY7nrFxPyeoSlDiobNXX/AdtUCaf8+sw/WiX5yqm9ThZSQdJj83nOYpJD8/X5YF0fdpcWM2YDzxpp/qTnrva9F7lAya+77A4HyBiiHTCSFrEKkCJz3icMBqFxHGEUoogaNNqtQgCP7vGDiIOSjmZMKV0hfL7oNLkVsW9SEOoJVt+ZkqhN5ib+pPd6hU0qrhHCif7yQZZsrVIix+dMPH6p3dCcHBEpceUxw8sFstlya+e+FIe/DLFD/7Fmy+0KRaLxWI5D+y48F0o90dNxTuoG+aaNXXyJRMAsPl8wEnEZ3NWHaXqwqZURyVadWvR2SxGytuaw4vLXk/TsK9u/0zRU6peZd4oRKakW+69KnuRSzsm1mpTZLstJzMyhfhTFVtmCfTNElgVf5MK38rxW2QVLp8rCDoLF51kWm4uXwkbrnuPqwU31U2TENrcSVg990yuYRCUGBQGR8eoRGESjagAxGUcGjwnFe/KMVk4bkKcgCFB63TOcxoSW/emp63Ur2f6e0ZIeenZ0rqUxdiU95fPI5fT1bmoxf0sz5+u3ONyJmSy61Rba3WT62uxWC4+rn3WYV69917mlN+4/433v5a7/t9TAOg8Ydg9uu18mmexWCxnhWuffZhX7rlv5rtuK17YepQ3vPI2/uS+ZxIf2t5c1EuBHSFKZyacoXk+4ZaitEGslffV1/IsH5OLhab6NwvHPRdMheFuURY2m79a/VyESU7VnQvS6boLf96mInjzea9lO2fN8236u2mt0fr1qXjbc3tzR65RFBJ3E1Faqjx3AFfPbrO0wDOYsrm8T9JURYLBMQnKJJhYI4EL4hEnMY4SRDkoB4xoEm1INGiTZAMB2bIvGpq+TRWbi4GDzQZr6oMCTcy+V42lt9ifLzE0vZyRxWK5VPiWg5/iBxYPAc1Zdz/92Ru46d997PwaZbFYLGeZbzp4O/9o8VFmveu24gavx38+8Gk+u3IFD1hRemEoi46yLyf/7TiTENZZgrO8rynEteotYqocNHlIq/ZtV4RuJSgLqZd5J9O6VUXrVDKRTqWl3R558G1FSDdox+YEPM3n23huQjYHtsGG3NtbX66m4X5sh/o9a7K/KnzV5veiqsJLvze/Jk2ifiLeYaZH0uhMioLWCUo0c902KIdQg4QJRik6QQvXCVAqoNPxMEYThgMSnZAkCXEckSQQRyFKVClsdzb1gZf6eUxFF2xyHtshvw/l71XdQ57ul4mH1mKxWCwWi8Vy2bCjRGkTZ9oV3o4AaRIXs8TGrPq28vZtZUMe/JhvE4GZi5XMCs2tib1Zgj0P2S22mcyTWBF26e/Nw5438xJv77qfzr5ZbTeF+xbnL1TmIVe9vfnnqleuLrTr4dJlG0zDcVm0aukYg2kQ6fXxAJE8zDid+2nIQ18h8F1EXJRycBw3E2y5bzVPgiRbxrpOsjDnv6r38Ew8nbO+I7Pu4eT+NNVfrcd6SS2XAsYzzF25hrPF8if9YUB8+PIZDa/zSLzBP3zgW5i719m6sMVisexQdC9hcd86N/hHL7QpFyU7SpRu1RHdTESW2Uw0NXlNK2W3UV/dy9ok4LYVcrvV/roA20JozxKmEzlWsm9m+GXTPWhot9EWaXbD0Xy/ZoXkbvZ3eXujWMznrpILvQkmD90tZtLqwtjKPSw8pJuHjm/tuc7rqIULV0KASZNDiSGONeI4iOugtUaJoddqkRiPxHgo5QIJiTZoDdrkCZQcRDx0YmpzP7fngZ4lLnOPZXn4ZFJmy2qzepq+T6VaK4MFulTGClPLJUAv5m9f8JssqPamxf5Pv8ePPv6dl22Crw9sPA39DX32r9nQXYvFcvGy/6qT3PKcP7jQZly07AhRKqQdVZMve7KNcMG6AGwUYlmCGVPZ2FxH+e9GoQtFT7wi3zJhUj2mvLxLw/zLsjeyEBGllnIvG1WvnGqwr3puTfJhcmwRTlrYVmm4XFHDtah6I/PrS8kDJw3HF22U7kNZ7qWrVOpMu2VtSC5uc39gk51Qd7lJdpwSVbQ3mcM58ZtKYXy6PdeWRY5nk7efi0ldWG1MLmwNeYZfVdSURy+X52xWn+T8+mkUgsZjhGsMCiE2Pg4OLi7puqTpkjBeEND2e4zHIUmoQTyU0ogyGCLARREQRhFRnBTXtfIEVi5f9Vmta7/iekh+fjMGIKpHTYlIg6lEc1dlvgaR9CkvP45MBOl2ow4slp3Is77kQb5qz+foyNaJLl4QHOF7X/NXvOv+5zN4aP48WHd+cQ4M+J6n38pruvcC3an92ig7CGWxWCyXOTtClOZIRTgxpUs3DbWVmu/PAGKKqkqVNLY7q41KuXodxmSJaur1pMuOGJNMDhSQ2kKn+bk2h8DOmItY9vROXaCZh01UenYkDedc/1wxfisa5qhW6suEaWFFMfpgUhGZKbtcpxtMVTs3nlOzXSprauJdLgvSXFxPai177iaXpu5Lzk+wLK1Lds1KCpS1P93hUoDGIUYZECNoEZQR0vmvLoiTeUNd/MAnDKP0eVNuNidVY1S61IujPKIkQWSS7Cm/juUBi3Rf80BE5Wyz6yN1VT1dshSy3FCwdLnSlssbTLVgaWDCYrlYMa7B+Jq/t/82/t7cKerLeTVxpdvjJ3Z/gc+tH+SWJ3qokbqkvKa7Fvr8xO4v0CRI7wkHfK5/EOxccovFYrms2RmiVNLkQsaA46Sd+CQPHSx5QJWaTlaTLoUxHd46ERpmywy+9W3bDcOdta9cT0mGNZRLbWzy+iqVdmR06To01pFVX5VK05xJGOesMmdyTepordPlTYzm4IGD+EFAOB4zGg4ZDoeESYg2oMUtZlBu16bE6JIOmw5pzcvXE+pMLe0z4xkp1n49g07jxM4EhcZFMNqQmHRflEBiEuYX5nD9FokW+sMRwzAhd0cHrRZRFBJHYxKdpMvJZOI0b2NmFuZa+PR2bJ0OT6+KSWNST/KmIcNTA0y1zXlUg/WQWi5y9t14nPc843fY5wScbubFX7vmgzx8hfD6D/9j1NrO+M/zuSQxmu/89z/K/g8+gu4futDmWCwWi+UCsnP+qycmi32ceHJOq3MqlSPTbaWEN42HbNNrukWzjQlxUmFQW/6jHm7a0MZEYE130KfK0iQStmarObdbsVmiou0eq5TCcT1c1wXlYIzgegFeojHa4CRCrBNGUfPoeZOQz1Go4opMkh7VhdV2Rfjsc6hfhsb6Zl0rkyBohHR+qDGCI2lSI8fxQBxEHHyvhSgHcVyMAa0zD7PRCBoHPw1718m2RXKTndtZ67a8pmgafkvxpZOSx7TSVv34WkSDZGHWTUvBWHFquRhpuTFXu70zOnZBtbnRDXnOjY/yxeO7GT0yd5atO78Yx7D7hpO8cv/9M8u0T2rix6wgtVgslsudHSNKc58m5HPapsVDHvZZ8UQagy5FGBYRgPmHYj6joRxduFmYbqN9M7xGs5Pw5PY1hNlu0U56nJ7aXre36N4LxbnlfuGmhEFbeXZn0XTOTdlqy2Xz8rO8ca7r0un06PbmCcOQJIxpt9sEgeApD3AZhyFhuE4azlpd6mSWmDakc0rz8F3JvaWpK27z8z4Nba91LsJMowe/XmXFSwuIaJTRKG1IEtAGXOXhugF+0EUbhTYO890FlOsgjsN4HJEkmiRO0I7geQ7G0yTxiNFgPHVOU3M8a/csvz+bZstl8h2anJOBfB4wpagEM33/VXFMtX1TpCpOn/XpSAeb6MhyedJRPv/npj/nN/bu598/8oYLbc6TwviG9zzzt7jOOzORbrFYLJbLhx0jShv6vk1FZoszqXlbMmEqQpo4Z8bcxCZxOcuTlIdunovOct6m1rp0jlsfp5i+ZmfDuq1Ft1TEaRNN+/Jr2Ov1cL02RnzESa/pKNTE4wQdRbiMEdEszXUZjmPGUTLVflMb6bPgZOUmwlFIKsKo8dwKcV9+xpoHL/JBh+knahtI+sVTpO15vg94SCZKA79Nd2EJ12sxDmOUNijH4DguSuXJljRKJcSJQimXVqtNrEPiJNq0aWMMSZJsWuaMyAdFSgMYlUGgbFBITDrnVxuTDT6lSZ6Q/A5N6rGeUsvFhG5pfuAVf8VLu188K/W9rnsfyVf9MW+76zWMH7WizmKx7HwWbzrJ99/4kcq233ropRy9Z88Fsuj8YALDm1/xd7yi94ULbcpFzY4QpXnWUzPZUAm5ra+xWFdr5SDWXCZMtEVac56QSJgttE5n3uXMsqXI4TNl4uGrVJlNkZx4QvMzLs63dp0m55SeeWUlkqL+aU/nmYqBangnWZvNYbOu6yHKITGAuIAmihPiRJNESSrCFPieSxwb4kSX8mBMe9GrNktx7ydqSabOueksU50ptWcwL18SwnkbpUoKj3j53md1mdK9AlBicMgyKisXxEsz8kq6Hqnn+jiuxzgMMYnGIDhuOj9NVDaHUwtKCWIU4rikybWmw2DrbCdUt3xWZcE5SXw0XXfjlvKk0dxbbUp1lEPcaw+o9ZRaLiocw3cv3M6BMwzdrXOl2+OtC4f54J5j3LHaQq27Z2fE8Tyh2xp3PsSb8Yp5MNrg1tFVuAOb4MhiuehRoOdinrvnMG9dOFzZdffeh/mjx5emjzGk77VL4BVgHMN3L9627aiQe6M+d44P8NrOE1suGXY5sSNEKQBGTdwokMYzFuGB6dIRSUkHlH8g8zhlIZ7aTJYRqciP6q9U4GkzpU6ahJlSqrI/R2TSqc772obM+5N3xGfQNNd10s4kuY9K/0RUOewxPT+TiyhjSAq7qqJtM4/eVvMHN6P52FwE55+raJ2GaiaxIYpCQh3j+S1EFNoIsYEYaPlzGBMT9tdoKYdO4HO8H5JgEKcqKqcEKaVlTHKPLqmwK5c0U29CKRR1esXU5IwKEZUVVYLO7q8gGDHF4AqUnyGDkQRQYLxM0Bo8X3DxcHSHRAIS4xJGgusKGIfB2gbijPBa3bRWk55V+tQkSBbS3PJcIjTrQ9CJ3jQctzjL0xZ8pYy+pjJ8VLmaCEj+sGKK76HOQtGVKBJiEp1f4YmtU9+Fi6jzbbGcS/73DR/gvms0r//QP0UN1dYH7BC+9cW38RN7bmFBNXfSvvrWH+T6f3SE1sod9utusVzk6PmYv/zyt7HP8YHqMli/sP8Wfmrv304dc1JrXvsXP4xa3TlS5Hzxuv/7wzz9pw/xuQ8+xE/tuftCm7Nj2GFPQjnMVgrVUXj7Cu8XjZ3W3FtYkSg1l2PRF6/UuTW5yKj/nmFKZavU2pl4W2m0te4FLSTeJkKivmdrD9j5D40sh0CLOChUKrS1wYhGa4OgcByXONaI0SSJQSlQSvA8na/y0zifNRffk5mMZa9zPkxQ9iQ2ifeGv2shv5INAqS3Sagk6Wq67sYh99g72bmYRBNpTRQbjOOAcmh3OnTaXTqtDrFObcaYYt3WfMDDAK4CR8BJwGhwnOl7vh1P6Wb788Gg2l6KNVArns3mwZzK8dklqkcCFLXanqnlEuXfH7+Z//mZl09tV47hfS97O88NgpnHdpTPVc6AFz/rPu46uv+iWce0o8JNPQBx5JIcO3YeLbJYLOeC+RtWeO6+Qxx0AwKZzjgeiEfgNG0P+dKn38udRw+ydv/iebD03NC6Zp1n7DvCotp60PCucMjrP/aD7P07l+T4CQZ663WsLyd2lCgVQJcS9QhV8acyUSoNvddivmCpskq/V0pu1nT9DSaaYxNvZi1xzHYTJJWdljNLVkJxJ0Ko7NlU+dw8k3qetkv1nFI1sFmyozqblTvT7KjFfVTpPEiFwjGCTkoeM3FwnYAw3MAkMSTguoIrgh8kOFqIk1TkmdqVrVw7U79fTiV5lDGm4v2eLXKnQ48LW3OncCmcVXIBWXoAxCgQ0iVglMJxIBklxLEmCkOU7+D5Lstz83Q7PXqdOQajkDgpeShFkKxBI6m4DdRkcMP1hPx0yjY2JTuqiM5NQnmL79Mmj91kkCb1iJavKSWvfmPdtbnJ+SGz7LFYLlZ+/bYv5Snf98mp7arT4YMffzbP8u/BkdkdmiWnw7uv+0t+Yf4m3vHwl1/0kQSR2X62cIvFsrP5oZv/ku+ZP8rpLoHVUT6/e83f8huL+/n3D7xhsuNiejcIfPtNn+Jf7/480Nmy+F/2n8pN338/en0dNhmMvFw5Y1EqIlcBvwvsI32E3mGM+SURWQbeA1wLPAR8qzHm1Nb1KcCkc+ygiDGviMJy+dJnk20w5ejKfF/Fy5UdqHK305k9+bNEWe44q8yjMxNjykJIREDlmVil8lPUd4aiD2rXquxhnnEuZ9JevR4RqSVqqp6PyaKZNRBHBvEcfM9nGIcYA+1WG5H0ciWei0kiktAjSsaEwzHajFDKoRMEjCKIdbPtdc90PtxRD2t+MuK6LExzIVpkqqUchi2IStdaVWhIQnSSkIQa5fh057r4rXmUG9DvDxFcWl4XR7npfFHfR4uQ5KHAWmOSGEOEkZBWy8VNBK0N630HY8zUPci3le9J00BMPXFVERGAabxWefnynO9Zc5Kntks5tD3zAZuyN3rnhCme7XedxZKjh0M+/M9ewf96xZfzubf+8qbCFOBNC7dz89c+zo/f/o1Eh7rnycqzy8dHCT/0U/+Ymz63dlH1PS8X7PvOcr75+t797Pq63wPgULTEL/7NV18UUxWcA0P+w/P/kBe2DgM2Gd3Z4Mnc9Rj4UWPM04GXAP9IRJ4O/DjwYWPMTcCHs7+3JO+uph386TDKyrTIrEyTMM1/yv+xqyR/gSIckpp4ahKGdRqTJOU/MmXR5JzK5bdot/65aGSGPRXBULt+Te1uZ9+ZiNVZ3rlsL3lIcjYRFkg9piIOShyUclDiIsrFcQOUkyb/iRLDOE7QSSryFdPhn7POqenazxLN5W2b/RTlyiKX5vDffECgGAvRCUkUF+fu+QGuF+C6QeFxTLPjCiIKJenc0clzkM01Nhq0xlEK13FwXXdLD+nUHZkx/7ReR+PdrB1b/77Vf6ZtMM3/y0cutpiPfZ45q+86i6XAGNwPf4qDHxnzCyeexmfG402LX+n2eEN3g04rPE8Gnj7GN7BnzD5vtXH/0WSO3f/vAcztd51nyyzbxL7vLOeVvU6XN3Q3eEN3g2/q3UNnbx89dw5WCThbCJhdIdfvO84399bOeF1qyzRnLEqNMY8bYz6dfV4H7gGuAF4P/E5W7HeAN2yrvsocTBDV0MmnFIVbEpVNNO0pTSEsREQaSnr6l2FKzGyyVmVefsoT2rC9vr84lmkBdT6YFcKae0XzxEU5juPgOM6MugxKCY7r4rkBjuNiDPhegO+3MAbiWDMexYBDrOHU6jrrgxHDMMZRXZQJiIYjxBhc1y3aK4fuFuteVs5hkzmjM/5u2l7ZR+k5K4RXLdmQAXQMJsFVEI/GjPtDOq027XYHNwgwqcxm1649dDtd4jgmSRK0NiRJeo0xBkcpPOUQOC4OYHSMqxxc5aLEATMJd89tzO9P3cN5pphyOELlmkz2N4nd6vZMVJP+GJNgTAIk2TaDIcGwM/6jdLbfdRZLHfevPsPfvXQ33/zRH7jQpjxpugfXufNV/4N/sPDohTbFcgbY953lQnLA7fHpl/w23/Oij15oU2ZiPMP//tJf549u/j8X2pRLjrMyp1RErgWeB9wK7DPGPJ7tOkIaAtJ0zFuBtwLMtbxSp1kK8ZiGwk68NZK5QAsxMDmk+KPJVylZ6GO+bqISlcXamiI50pR9td+TEMXZnkigsjZjKoSycyJNWGMqIba5t60s/ErXIT/n7FNlTmRmd5HtNbctr7liozTPDZSGqyZ5uyUxh2DQs8VZ4cXLPHUyCWk1pIl98thqQxpKmugEMR6O4xEnaZIbZRTGpGJMlEur1WPvvisIwwFROGQ8XAcd4xDitRWuo9HGxYgC8UhMgsEUCZwrpyzZs1M5h9I5lZ+hyuAFZKvB1i7edEKt8r0Q9GQgQcBzhHbgMOob4iRmMBzjJg6BtPBbCtfxIBHEcVBZ4iOjpIgAKBJCaQ1xguu7BH4XcbIESuLiKAcnW0fXmImNlYRapXnXk8c+v+Pl0yw9Q7W4eVOaK1q50KXva3VHVnuxLxem2WCUNpP28rVli3PYWTzZd52ztHQerLRcdOgE3e+z50MB1228lQ9+1dt4mj97ftK3X/9J7th9FQCfPXqA/oML58vSLRExdFRz8o6X3vHNnPzkXq5f/+x5tspyJpzu+86+6y4vZN+Yl1z3IM8NHgXO3vzIQDxePXc3X3zJXgBOjjt8/s6rkPj8O2bqtK9d58UHH+Z6b0QgpzeF4jm3fTvRp5a4OvzUObLu4udJi1IR6QF/APywMWat5pExItLYtTTGvAN4B8D++Y5JQxRTX0ke4ZkKnHwZFFDlzjWlcFVTT3lTCtGl0s9OwyhVvkwIRUe5Mk8QSvMSJ4Kq2JkekJ9HdXP+u66MMiGsa3VX18LM5vuVJ6LqLNepmfiS82uclsq8g6XGp762Zvb2snicJg0hnUyUrZZq8jDrTGyoXGCn6jZrz6C1ARLiJMbzwFFemnnXQJqMKF3SRykf33dYXl5kY32VQX+NI2vr6CjGJcILwMUlpg0ojHLTNU6NKRL+lLXTtKc5u28qHwiY3OPqvRNAVYRqU/bY9MC8Hp2JUpXOCxVwHaEVKJRAnCT0+yO8yEFUTKvl4OWiVDm4bkCi0mdYk86vVI5gYgOJxsQJXsej3WmBGYAGVxxc5eAohziOJ891dm7NCYRyz2V+f8vitXJi2a9JWG0ldLf2HShfY1V7ZibhuVkj2U0SyqtBVT3dO4Wz8a4Lrr5q552Y5dyjQLVa6PG4cRA0Z+H3Ps7yh3bxsS+7nmvcR2aKu3+xfD8s3w/Aj7Wfy+8/8uJ0hxHkAq75ZxS4arYB8e/v5drfvOVSWJbwkudM3neVd91V9l13qXPV3pP83rV/zdkUpDmvbMErr/1rAO4JB3zNF364CHeUNKDq3CHpu6yJ117zBd524JPA9gVpZBJW9Yj5352n8/6P7ZyJSTuQJyVKRcQjfWm90xjz/mzzEyJywBjzuIgcAI5ur66Kvyb1zmWC0xR94npI5mlZW4T+mmoPvSJMgbSvLKVOdllYzSBPJLOlFSZztpbk6Axzae7ibh9TESbbZ+IlPZNGK07H9KYWnjBwnHQupeu6SKYefc8HFC3lEARBmpgnGTEcjlhb2UCbBK0TRBzEcQFNHDkoBK9lSExEHMUofJR4uUTPTib3kDZdzHzdz/LSJ/nNrw8zbA8HMs+twhgh0YJJYnSoMeOItdUB/Y0RruPSxUepdAkcx/Np9Xoo5SCicJxUzkVxgucG+EGbkR6QJIbEJLii6DgwHCUkYcx4nJDoJDvl6oDJ1C1qmOO59RziTLRLdRDnzMTjRASX20/n0u5Mzua7znL58Z5X/xp//PEv4dYfegHqb27ftGxycoX3vuUr+cXX9bjn+391y7p/eNdH+Nqv+wwAnx5ey3/78OuQ5Px7FIxr+PHXfoCXt+8H7GLwFzP2fWfZSVzvefzeV76dBIU2iu+79bsxR1rnrD29GPFrX/p7dNT0HP/r3Q1ON6nRKz/7rfR+fp65z31xh0xK2rk8mey7AvwGcI8x5r+Udv0x8Gbg57Pff7R1Zek/aV+47K3MQ1yz/vCM/86WvZybtVF4QMvNUq3Y1P8tCcjT6X7Xs5WWxXZ+brktmwrAXDRnInV6aDILgazVUb8e+fI61apLIjyrY8qU0zhpk3m88ts4CQRuctVK8T9HKQQnnd+bhXCOk6wOcXAkv1Iq/REXrYU4FiSKQClc5ZBNvSy8f+VBhWmhJsU85aKsgDG1p6QSUt1wXRuevVQHq/R6Ako5oDXjYUgUxsSxwXVS4Zs60VNh6gapODfGpCG8pPa4ysEVFyUKI4KjwFEGJQaTaIw22WPSLBK39f0olZ2xh9zjKo0PRUO7hVe1dm1Mc/kzSa51Pjir7zrLZcmLAo/n7Pk0r+u9ZGufgk7g459l364X8o+/7sW8Zfff8fxg9lp2B9weB7L/ki+qz/OOg69Aa8EYITrWRqJz/13S8zHdpSFf3rmXGzyb9ONixr7vLDuNQDxeXmhQzY37j/GgswuAcN1HrZ3F1S33jLlizyqvbm80rrl6OoJ0VQ/52aMv4+Sn9zL/N7dYQboNnsydfDnwXcCdIvKZbNtPkL6w3isi3ws8DHzrdiqbeErrIi77N9u/nc717JDU7f3HuR6p21h/w+fNbMulTjk8UpRMlsCZYUS5fiUOkwyllDx80nTolkxlV8090kwEnEGnc3C3Qfn8jC6J3JJmniS80Qhk8yA9BAUmXTJHOYqRETwvYM/uXYThiDAccvyJI2iTpCGqWtCJpj88TrfbZteuXQz7QhxpImLScGkn865L4ZUtC7Q8/LgQsSVR3iSKygmDyp8ndWZXMhvNUI7CcYS5oMV4OOTo8eOMRwlJIrS7PbygRZwYXNcjaLVoz/VIEs14FKJ8D0cUngdKeSgjuCgcpXBaLoEjKJMQhxqTQNBKO61RFBWJjsq2qmKuafPTsdX5lrZW56hObv7k/Ms7K+G6E/f5Vt/j7UYenCfO6rvOYtkOwQc/yX1/7vD33/dm7njRu7Z1zLP9Fne+9HcBGJqQ5/7ND2KOnvu18L722XfySwdvwRErSC8B7PvOsqP505s/ADenn9/yyKv46C1PPzsVC/yHF7+fb+6ewmkUpKfHR0ZL3P0NB7n28G1nwbjLgzMWpcaYjzBbt3356dQ1EZ6TTn1ZjGYNZt7SZo9gU6d6s23GmCLpUC2QcDrctebtrNezXSY+t5K3dFMvacm4kvZsTEBTP7SpXsOUNyqft1t4kovkRhOL82mHZyODaxqa6tBqtfCCFl4rwEiA0UISjjFaE+kEpRyM0ayvbWRzRBXzi8tE4Yg4HDDs99FJyK5du3CUYWV1HYc2Im4hkIxJ0qy0tYRMdbE1K4FT5RrN2F8pN3lwMYkh0SN0nOC2F0nEEIUhURSRxKlI9HyfXm+OdrdLq90m0Qmu69Fe6hRzXZM4Aa0wiWCSCNERLS/NYpwYAfFAGRxHsvmr0jzXV0/P05wlRJuvSXUqXCEzS/NTq5PZ8oe3/FP1sTYvFbPzOJvvOsuli4SKt9z3bXzl3nv4keUHnnyFxmDi+LTnH+Vrnbbx+QfP/gh/d+JG7rn9midvTwN6IeZrn3Unb1z+xJZrrFouDuz7zrLTKb9rvmPPrSy+cjiz7D2r+3ngjisq22T/iK95yvSSVEoMzw8OnZXBtad/7Dtxbp3nypOfSaNfLNviLPq8zz4VhwvNgnSWqCv/h7weQlsvV18qJqu8Hnw6U0RuZkeZsvd3W+GJhSA1pTmPZ59ymKsxBlV42WQS2rstTDHtsCLsSiWUSkWT7/t42Y/BR2uDDkMSnZCYNHOt1tAfDglaHp6nmJtbYDzyWU9ixvEa0Tjkis4e4mjE+uoxem0Xz0vX9SyyzyqmbvxEnGZ6vJzkqnJfmsVq3WNaRucx1iZB6xBMiCNziEmIwyhd6sWA47r4vk+n06HVbuMFAVob3MCl1+sVib7GYYSODAkaTIKYpBCl2igMLiIapSZLwdRtaxLW5zJUtprMSBfPVTEvNW21YsdOF6YWy1ZIJHzxjqsYP9M9O6I0YzTyeCTeAKAjwm5newk2HFH82K4v8pz2I/zg3W9G8iQh4dn5vhvP0FsaZB7SzQXpQIcc1yEqPitNWyyWC4mk3//AufBf6K/qjPmqzidm7n/n3C7+zeffWNl27d6T/LeDs455coI0f9fN/fEci7/7MZvU7TTZ0aJ0KzabK5eLya063KZJg+SCTGuMlEJSp32o27ZnVvntkIYtg3mymY82a7vsQaYkZk63XlP2CGfbst/p/Ugz0kZRhONpHJE0MZDWxFEETupJXd9YR+sEVznEkcZoTbc3jyjFiVMnEM9BcHni2DqeA74/T6uTilelXZJYEyc6y2Fs0LX5uyYLsU2zPgtFXuTKdTG135Nr1yj4DIzjKF1ntD9mvid0O4qjRw8x2BgyGvfx3IBO0OHKK69GlMt6f4NdxuB7Hq3WPI6XfiVd3wNHQStAEoMkGjNcwdWa/bsChtphkAhhEmG0pu3qQmA3hb5WIgQ2CzM/iwI1XcKoua3JsjVWkFosm3HTj6/w1qXvB+DBN87zhbf82mkd/8rWOn/0Nf8NgBXd4s1/9X1Peg6WUfAvX/MnfEX3C9vyKrzxi29A/8gSux76vJ1XZbFc5Oi25tde+zs80z/BkxVx55rXdw/xrK/9pcq2RRVzruy277onx44QpZk+IJeSaa6badE0s7vc6LVq8HyZ6S6yMBGmUtQlEzdaqf5cbM3qQ+fHm1pDdZFWeGDrGWBqlOfQTpaKKVoqKe+pipssy0J0KydbHKbypDvlEFRTrbxYXkXycM6GCzp1wqXrWCTLSdeMVaTJenDSfY7jZB7C1E6VzjRFJwk61jhOmryjN79A0HZJojHD/gBJDI4SRmFMnCREOkrDYFsBcZIuN1O+DOWo8IrRAnk2KUO6NI3WhljrVGCZ1NPrKMFRDolOMCZdykQbgzaaOIqJ4wgdjxkONCY0JLFhPA4ZRxGiFUZFxEmMQpEne8rDeZXrIk76g6NQDogkKAxB4OAaDzwHHaeJnVzXS+fvmrh2ksVdK0K0y77/4hktJv1mz4bJnwiyp8EUR0weLdPwjJU9rxRJr8oWVb+fUnhQG2acMgn5tVgub+KHHoGH0s97bngxX/fyr+ZfX/0nvKTlbOv4jvJ5dpYnaaBDrr/mKMc3Tm99vTqO0rysc/+WSY029IgfeOSruO/Wa7judpvow2K5JFCG5/gnOOBuX9hFJuEfH3oFhwaLxbaOG/LL1/wxe7cZ/XEm9FSreP+dD471eyzffpd9150hO0KUAoUmyNfdrMTNQtEJbpz/p7I8n3n61azCqSRCUuvmymRu56TIRIg2ez6rC4jUQ3ELYVq3v/ynMWio2NcouE3qv8szsU4JdQCnJg4bFXOasAhkshgkxQqWRak0862q2JUKmrpIyEV6Naw4TzBF+QrltzOLo9WJRpPgKwdPwJEYNzAYozBhm9E4ZDwOaXkeOlGQaKJRSBiOWFtP6M51uf6Gp+B7Ch2HfPrTtxGNh+hxzEZ/DCYBIvbu3cvug/s5dmKNJIwL200+ZzYX5VlYqWSCVNBoBG0gTGAcJ2yMY5IoAmPwXaHdCui1PYZxiDaGtucR6YRxHBH1h5g4hGTE0ROrjPp99u/fTxQlbAzHxEmIcsY8fuwI870lFnu7cR0PJS5Bu41yXXBcEkehRdKMu3qIMRFzCwGCx4bjMEqECJjrtdAxhOGQfFSiPM8zMbXga0kHYcrP4mS/oRrtnIrP8vJISqf33NQXQ1SltVsNWYIpU8wiTZ/RyahGnthMm8mgkCoEsc5+LBZLme77biV6H/ybD7+B//e0D5z28R3l8+Gn//FZsmbrJRm+EClOvnmZ6754y1lq02KxXIxs6DEP/MjNqI98ZrJtzx7++qMH+dbe6oUzzLKj2EGidOKNBKguFLp5WGFdaJbrmRKxUHiO6nUbY9BaVxLFTAnOBudg4U9sDP2ssq2ETKa6rxyOWYipqYKNzZVKTUJMy1lmC+1YJE+qJpSaJLiZiIvN59DW5xZNFsGRbLBBxKB1jCjwPY+g7aONEA5jHK1QWuHgIeIQRSFK3DTste3T6rRxlMegv0E4HrG8tJvRYIPBxgpxmIbOxnHIqVNriHqcoNUh8D3GUZjZryGb/yQVL64iD/MdJprhOObzDzzCcBQyDOPMG2lQaDzHJfA9iEMUhjnfpd1ppT+uxuiI4WADJRC02hw/fgIRh4WFBTrdRdqdOQ7suYJWq0vb7yFKSExMjMZ1BS/wMs+sIYljVBIhSYjvu4AwTlzAICpBM0SbITqJ0Tpdz3Xy/JrC853PEU49mGnyqtOap2xKWXdLLtBJ6LLJrl51KZ56E/lzo0sZj/OykpSe1E2eZ4vlcmfw9oM8++p/WPxtBH74e9/P9y4cuYBWVXn6x76T4K/mOfDE5y60KRaL5QLy6rtez8k/vYIr77uf8ixUvbbGL/zid/Czc+l/8F/zHbfxtgOfvDBGPkkeiTf4it/5F+z9tB1QfzLsHFFaIhcvTT3TxvlnWQd7llCqZ4093bmftaay32Zq2yw2y/Q6VX85AU1pW76sx5a9dVO3jppYzuvcopqGAuVt5fDMtImJz9mY0tIqhS+6NFggYESjFHiug++7aCO4rovjxSitQLtZxjKFUi4CtII2gR8gogjHMaPRmE6nhxhDOBwwZoTWQhjGbPQHgGL//hae7xIyEVWpp698JTOhpCHUmv4oZm0w4sHDxxgMR0RhnIW2GnSSoEThOg6BjvGVYbHtsbQwhyzOMbfcAYF+HKHEQTyPtdU1PN9ncWk3u3bvZn5hmYW5JTwvwHUClFJoDImAqwTlO6jYQGLQSYwkMcokOJ6DMQ4m9oAEUQYkRJuQKI7QOiGfG1u/R6o08FL4u810qPnUPc//zb2feRCDTD8PxlSXD6pPga58D8mf0onXtCxiywMhFoulSu/3b63OiFIO7/7qF/Ky9nt4mt+5UGYBacjuFyJF8Ffz7P2Vj9kwNovlMufRzx7ghrd9jHpaJDMes/sdkyiKDzzveXzX8scAWFYh1+3wNY/zdx3Ap0ZP4cbfPEz84MPbOlbNzaH27GLO+fy5NPGiY8eJ0lnLnWwmIjfrum4mVJvq3I5HNg/NrUQXS6r9in61yf+ehAPDRBRvd0mZzZa8aXRFbYPc85on+dlebpuGNTxnDBDkdU9tlzzJjqHXbdNpBwS+SxC4GBStrsG4LuK12EjWQYPXCkhiIYkV6xt9wiQhaLdJxarHcDDCGEW3u4ASxXg0YH19FWMiTDKk3Vqh1Qpo+Q7aQGIMUZzOBTVK4TgejnIxGk6trfP5Bx/hyIlVVvtD+okCneDECa7nIU5ahxKFoxxaRuh5LjccPEg46rNx/CTPfeZN+C2Xxx5z6fcHDIYjFpfmaLXb7N6zyMGD+1lY3MVokCZvcgOXVtAhaPUQ5aJcDy8I0lD0OEaNxviu4HfbGCUkGpTr4LkG1wjjgTAaj3jk0cdYH25gjEbr8jOTPYF6cq/yaOzCw1+9ddO3tBIeXjwOjWitszD82vGbtJMLZa0n4b4Wi+U00An+dyd838v+GR/8r29jQbUvmCn/8NGv5Ph37eLA0c9ZQWqxWLbNzT96iH8z920APPgdB7jnB371Alu0Ofm7DkASTfzwY9s+9uEffha/+j1v5wXBgO1Mhbhc2BGitCzSqtlRq2WaBFrhDdpEWTUd2xSCup3Mo4UgzcNaS07direncP+U6t2i/q2W7pg0Uq7r9Dvx5Wudi9K6WN7suNm2N+/Lo6XL8xgTnYebph5THIXneyQ4aOXhD0NiFImJQDRGQJkEnWg21jYYjvqEcZgmCRInnYcZa8IwItGGZBwRjWPaLQ+dRAROJ02CFCckOhVBiXIZj0K0hjgyrPeHxKMxOhxjwhBPeWnIrjG0HMFxFGGSRv86kq5pBYY4iUkwaKU4fnIVP3AYhxEG8H0P13FwPY/xeEiiQxCN47g4Kp33rBwHx3HxXBdXOWn6I61RicbVGkcpXN9jHCckWdiu6AijQwxCGCUcX1khJsags+ude6dVMXu4cr/Kn6T0PdqMpjGI2veo8Itncd+zIhvKxzdNlbZYLKdHfOgwC5/r8vLbvo83P+Xj/Ivl+89r+wMd8o1f+CYevO0qrrvPziG1WCynR/LEUXgi/bz39j18ySe/jZ9/+vv5yk50YQ2rcTbedVHX8Kq2xgrSKjtClKaUPXZSETFCrfNb8tRNli2ZzHncSuCe6bIteahjWZBOLKTQjCKSrdU5XaRed93WssFTVhYxp3lDk0LlIyT/ODELJM1cW21XUKpZEVSFvy593lJbZ+VmDBZk83ZHoyG+36IdhzguOJ5Dq+2CqyAWdKSJx2MiNWAcCSZ2CJQQhWOOHTlKfzQgMQl79yyjnFTEDQYj1lb7xAmMh0OG/T6OSojHXeZaQjgeMxyNsyy/ilD5rK0N6PeHDAcROjH42tAW0I4QobNUToZ538HzHNajBCUGRwRUQozm1MYqjqdwWj53f+F+HAe6PUW33abdbjE/7xFFMSdPHWXX3t3MxXMEXgvHcVBKoRwP1/Vp+y1c10MBKtEQJzhG4zs+bqvNxsaYREc4zhgTDzDREGOE4TjhkcePMLfQpt32s3ueJkkSI7VntXSPa/c791g2zzWtuUjNJKw836xETQZpJrHSlWciayxPcjxlh5nx2WKxbE1yzxe54pvgf/znr+BffPv5FaXHdYj88wWuu90KUovF8uRofeA2Wh+A//Thr+IrzyCp27nEvuvOHTtClGbRhOiykCtHiGZrkJTFEaUyeSV5pzedf1nthU906NZd3Zkhv+TLpuRBuaYQg1NHlES1zpLLpKchGARRpdDKqoFVuyt2lWIo84QxpaRHqW2mmMtX7vhvM0Z30m5JcFTFvSnmjJaT2uTzgKeEhsnChPPPSqFEMRxu0Ara6DhGj0Y4QLszjxlDMjb4nS7K9RFxccMxrThkhOApB99xCcI2WicsLi7S31jl2LFTzM0v0Ol2OPJEOl8yihI21gckUUTQ9hkNxwyHQ+JojOMqugtzLM8vcmDvbg4fPko4jtGhJo4SFIrV9SFKDH4Abc/gugYChe96tP0g9d4qIfCh1fZpdQKOHTuJRtHpLLG8a4HFxTlaTprYaa7XZffSEnPdLp25BZRqg/Tw2grxNF6rhes5uCKM4wiTjBEnJjYaHRnGG33i8Qbu8DEMhkQbnnj8GCeOnwAdp57J0h3RBsRoiqVeZPaySqXhjOwvXdpevq+pSNdGV75vk1azZxAzOylWFg4spMmgi6BdyVsATD1hlsVi2S43vrvPC+/6QQBWngp3v+mX8WR7S8icCc+45U10/3ie3XZtPovlkkdGiq+5/ft47VVf4D/tv/2cthX94n5eeOAHZ+7X33iCTz3/vefUhjL2XXdu2RGiFEqd3zwkNg9lzeMBofyh+ncteVF5SYyJ1msIYTzNeaVF9tGiaYGSUG7q8ueCu2iPSSirqqnvKQHZsBakKbIL5+6vqjKviEIRJMuaimk6rxkuNKre5KqwmAhUVfq7OPsGt1d+XVIRki45E0YhSRyBNugowrgOXgfcGBwHXM8HHIiz+YZKSMIIhaReSgGNJghajIYbxHFMZ66LkoD2WocwDBGliOOI8RjW+yPC0ZjxcMx43Mf1FEHHx3cVc902ge8i2pAYIfA9okQzVGNcx9BpCZ4rKAWBq2j5DnNtHxyFKEE5hsBXeO5k4MF1A4JWm063g28SjElwPYXveyhR+C0X5fiIauN4CuVoxE2vjTKkSYWMQdxUBsaRJhqPiAfrmI1j4LgYcRkNB4TjMa6aZDnOr/pkECELzab+DSg9EybzCZvycEvp+djmnNLSQzNzoKVcUT7QU52jbWeWWi49FIqNAy7d668lfuChc9qW+cSdLH8i/Tz32ufzh29YxpfNu1BXuSd5frD9Bf3+dgQnkzQRibp1gaXfsUmNLJbLAYmFtfsX+WTnatiGKE0WYpyn3YR+4BHMeHxabQV/9gmCTfY/ctXL+D9PrSZEeo5/5KwkSbo/2uDOcH9l25N910kQoK69injRvi2b2DGiNKce0loXjfX5pOVy5aVcshJZmXM5aa2pq18rMWOuZtmyWTXMFMiNlmRuZiOYXITI5udfyfbbmKV3Oiw6R1dCrmfYJaCFQqyJm47WD0ZDwiRCuUI0GKKShI7fIkZIlGDo4opL0nJIPJc4GeMnCeFwyGhtnUQZcFPvebvd4aqrrmI4WCcKQ/bs2UMUjTnyxIil5Xk81+HE8RVcR+EohecrXM9BOR4nV1Y5tbLBcBiSJIYYg99WLPgtei2XIHDozfmcWu0zGkd4LZ9Op8P83Bztto/rObTbPqdOnuD4sSMsLczj+wFKDOPRiJUVoee7gCZKYo4fO8H62gjt+vTmFcu79uK4DkpBEvZRysFRQuAqfGnhBy79UcxGv8/o5BHi/jGctUeRdhcJuuxamENhOHFqAeM0eBfz8O5NE2ZRWnZo8jybYjQjFctFWG7peal8Pw0Y8rWCN28vL6+NTtcqRSrlK6HBFsslgCcO7/+3/4mf+b6v4vCrWujR6Ly06//1Hfz2l754y3KPvvlG7vzh7SUW2dAj/vWP/FN6tzwEwJXrn7ErC1sslkY+8bpf4u7XdPm57/hu+Phnz2rd1/7iHbzj7S+rbPvCf76C+1/zW0+67tf++T/jaf/m4cq2J/2ue9ZN/Mv3/G+e6a8D3SdT0yXJjhGlmy3T0iRMyyKp+bj6McWnKYFV7rBvleyo3mZ5KZRZZTdj9hy+mgCnSYiaIsttPh8w06TFMTQIx9NZlqZ+TOU+1ewrK+z874rjVLJQZiENX87q0hp0YkjiCAeHwHXRrpCIInYdYg2iVZqEKE5wXBflCspzaLXaeJ5CSUwUjoijqEj04ziKxcUFAt9Dn1ohiSOSOMb3PTzfw/d94tgUCZAgXZZGJwkmSfB9hee7eJ6H5/toFL4X4CohjGIgwU9c5rsBnqsIXEWn5eP5AZ7n0Wq16XZ7OCYmjiPCMKLTdvB9j42NVfygQ+C76QCCGBQJSRTRH0d4ki7jYhB0okmiCB2P0dEIE47QCCaB0ECSxDiuixYpPOmTe2YqXvJZCb/K93V2IHl1/nb1uInnE6mG9JbtKQ9ylD2jRStWiFouYa52e1zdPslh5s9bmyaO0wQiW7Dn01dx41+9ZVt16lh46j0nt1WvxWK5NDl8coGfeOLZfM/yLTzFmy2wdjtdnk4f46iz7iLS/T70+5VtS39zAzfK9t5lm7Hno+5Zf8cZV/F0f53djhWkTewIUSpsTxBCVRzlNK09Oi0a8+O2541pFq0Ti6shws2Zgbeqz0jegS/MK7KWNmQ5mgRUFiGXZR1Ykrd5HVnZScjvbJtmsekaq0JFBBVlhHIcdjXyM5vjqBwHUVlynQSS2BCFY5TfouMLEgmxdogdj1A7OImbilKt8fwAp+XiBS69Xg+jA1q+sLG+yng0JEliDAbXddmzdzfdTovYaNbW1hiPhszPd2i1A4IgQJuIKI6J4gSlHNqdgDgcISai5bfwfAfXdfEDH+V6LC7sYjwYsL6ywsCEtAOX/bvnaXmKXttjrtPC9QPE9Zmbm2d5aZHBxipxkjAaR/i+T6/X5fjKCdrtLu3AJUzShEouhtFoyPrJFZYWFnF8P80knMTE4RgTjTDRmHg0Iow00TgmwjAKQxzHzUKapwJ0G6cTz/6uTOYOFxmVcwFZFpqlMPtSrWk9DV+p2d+P2c/gdp5Pi+ViwxGdzlHYYXh/8Slu+Ivtl7fBZxbL5U18qMN7Dr2Mp3zNEZ7i7ZwBql2/fgu7fv1CW2E5E3aEKN2M0xFOWuuSuFVMAmSltExGNfzQqXUOzsRTU193dFbI8ey5qtsIdWTzIGElKg2dBCQ799M5kzz0eTse60kW5Gn7ilQ7aQabive2fPUTrYmThDCOCPweWjz6YUxbYtri0g6GaBUQ+x2cSBhHCj3Xw/VclChcV3AURFGEkgTfD5ifn8dRguumiZS63Q6Li3O0Wz76UEi326LbbrOxcZLhcMTK+pDe/BLd3jz9kWY8GvH4Y4+xe7HHrl3z+IFPFBv6o4iN9SFhpDG6hdEaIwGONjjGpeN7qE6AS4frn3IdCYr7HniMo0ePsLJ6iuXlRYJ2lyu7PXw/IApDFjtt9HDI3Xd8hl0H99OZn8eP+mysrXD08CG6QYCrFKvDMcONPsONdYLAx026rEsXIwpw8NodXOWh1SqGGExSvVdNN6p0P7frzSebm1yMc0r1WW/yxjc9R5Wlh9IRlspcbOsptVzsPPTgXp65/ib+y7Pf27iUwXcvfpJ7/+Jr+Oy7Xsa+//axC2ChxWKxWCw7j4sixeVmXtTNPJ3V+anT22f95PWWO90m65TnXqRKQO20c2rLc9k09FikoYqGSqXUeD5nc+JyzbyW0yHAs7v9tXDcTSh7iiulS0K0XlH1WqYewDAcY3TqbQ5jIUkEo8F1NJ6r8TyD64CjJAu5DfDbLTzPSwcUDCSxTtcbTTIvrFK4nkurFeC6Do4j+J6D5zrpmqGuh3Jc4kSjlGQhug6OpEvOtAKH+bl2lrxI4YqTroE6jhiNIsbjiCjWYBQKIUkiQOO6ivn5HnO9LiaJGQ4GrK6uEScaROF5LaIoZjAYgDZpqO76KUbDDaJwhDZpCPN4OIAkAWMIwzBNCpWEKNfF8VrgtEBcEMELfFzfI/0qVwXeVjex8K1L+tuUBjLqeYpM7ahyISnf+HKb5e9sQ6RAJWWvxXKJoPoOw4fnOBwvNe6/2u3xu9f8LRvX2FmYFovl8sATxamb2zjPuPlCm3JRsKFH3DaOWB1dXuuY7nhPKUx7GutCrsnTWJ3raTJP6fbamu2tafBoFkIray7PgqqbvVCzzqFie7qhogpEBFWfF5j/YypHbkHmOZ6YjoigtanVVZsXWr8kBijnxim1nofwSh4Gik7bzOcaZucxHAw4fuwJ5t0ObkcYySIq9sBxWeqlyX+I+7ixxksMgdcm1IqYAVEconVMJ+hy/NgT3Hfv3WgdgkkwToJC2L28SH80RBuX6684yKOPPcFjR45y09NuwvU91tbXUzHqapbnW4x9Q+B2uPKqXexeWuDhBx6ipQKW9uzh5Il11scjhmpMFI0Ix32u3DUPIjz62IO4Xhri64qDo8CVmOEoZhjDrmFMFAsra33WT50kGg05cOAKdi0vcvUV84z7p4iTiIUD16MCH1cMgQO+MkRxhNYRohLEa4MIurcL4j6OGbOw2EH6gjFhMeMzz2irMYVILc8D1vlNldyfrouYW2U06dJL+Q0vC0uT1Zlt1uliLo4IaS7kUgh5+VglRUS3NqaYV5zrWF2aD10cuen30GKxWCwWy8XCgmrzZz/zi7z1wTfQf5UD2k4A2IwPDvbx43/+95Dk8hq13zGidKvlWeqJWXLK80nrIrC6TMxsQbgdW2ZmpjWZu7mIRsw/TNdbXrdx1lzNPAGMQ9XLWewvl5/ojKLB5qDdrcM3Jyab6eJFe1V/Wb32LBpzErJbOrzJqjiJGY2HaCLE0bRbDkHg4fo+IyM4KHzPAxPjKs2wP4QkwlWSJvUxEI7HYKDb7dEfrBLHCZ7rosTHcdrMzfVwFBx+9ChhEtPutUl0jNKKTqeD77u4roOJHXSi0QkEQZve3DyO66TCS48hiSCOSKIEnQjGeICDiEKhcJWD5/rs2bcPx/O46vhxDj9xCr2ygU4SnFbAruVdjDdW6K8OOHb0cXQ8pNdxcNpz+DphtLEKGHrLu1FegDYQrZ/CEaHVbmHiiDCO6Pf7uG6C5ypOnDzBxrA5xXplkIDqYEZtWKeyPR8PkXw+sDGINHhFS773crKj4llgEhlg8vZzj76plps8y83fc4vlYuO3H3kZ9+55gJ/a+ykC8S60ORaLxXJB2e10WfBH9LcuetmjjULiGZ3nS5gdI0phWgzWxVuTmFRKVTylZeFXrqdMXn56CZntU7QDiKiiM582mP4za05d2fZZ4cJSs82U/q3VWJovu33bZ1MNd04/N3mqJ67nske1LExzVZTbXrczSSJGJiGRGOVoWi2F77t4QcAQg4ui6/k4Cvw4Yrjah0TjOYokToXpaDgCY1hYWGAcDoiTEN/3yIXT/Pw8cRxy5PgJHMelt9AlisegDL3eAkGQZsqNxoZwFJJEhiDo0Jubx/VcdKgx0QhJQkTH6EhjjEIIUOKilOA6Lp7jEbg+ew/up93psrK2Thg/SH9jTJIkuK5i/749HD/8MEk05OjRNeK4T6/n0FuM6GAYrp7AUW3md+9F+W2SJCJaO0F3bp65zjLrK6eIx2PW++vMdT38wOOJo0cZhlExX7rs/d7sO1AkI2oaPCnf89LWiY+ddP6y6Emb0vAMFrao4g8phaabItZbKsK0yV6L5WLj0bv28+6lXfzYa29tFKXGAQmC016377JBBPF9GjOnWSyWixKFQbUC9GhsvaWWKXacKIWJl2SrBEGbHQ8T0am1JkmS4u98TdOtQgQ3S0BUzA2F1FuaLXGimUzGaxLUmwnhzc4zDZDceuPphj02nluRHifP3NrY+hST+YgmDTWuz2ete4oVoAyjaMhw3McdrxM7HgYXOum6m0Md4iqTelJ9hQt4CIHfI4wTjmw8wWA0ZGV1lSiJcFwnW5sUPNewvr5CGI655trrGY9HhOGYwPdIkoRDhx7Lls8R4jG4orjmiivZtbyHxeXdvOBFL+LIY4f5/O13cd1VB7jqCo8vPHiMwTgmiiLm5pZZnPNxWGPXnj3sP3CAUGsCV/Gs5z2Xx4+cYGP9C7jtgE4nwHEVV1x5kF7X59TKGq7nkGDY2FhlHI5xH/w888sH2LXvOtyWi2OE/YtzJAbGa6s88dgj9PvreK5CoxmFIRsba4SJwXF8tJbCUz7lHS1/t6g68xuHOkoDO6kYVaAMkg+cSP6cV+Pim6IRjKnmBDaANGaYtlguH97x9b/OH778Bdz/D56O/szdF9qcHYd56bN55n+/k3+z9D+4SNJfWCyWLfipgx/iHR97KR98+yvY8/ZbLrQ5lh3GjhKlOZsuQ3IGdZzOvu2Urc4ppfCMzjq+yXO7nfDgLW2btX2bYcpNbedzcaX8WSqRuwWmdN75x3zurskFeykEtOkMDNAfDnEcj153CZNEYDSuo3CUg8HB4CJoPC8Np03CBFd5QJo92XVcXM+l5/RQDiwszCPEGB0yHo8Zj0f4nosxHsYkOI6L1hAnCYnWJEajQ4XjB/S6HTqdNu1Ol07LIxqOaXdatDpttPGY73ooSefIeo7BURqTaNrtNku79qBcB1GKTqeLHwQo5RCGYxKd0Ol06M7Po3VCZNI5wo7vEY1DomjA+uoJXL/N3OIGYRjgIbiOQzSOGI2HDAcbhOMhiE6XiokMiU4ml1YmAwqz7nM9x1A9Wrt+l6qe0okQNfnfkHkypkPnc2+1KW3LRXNDoD7FxFOL5TLgy9sJz9n/l3xH92k211cD0ZzH/7fv43SUP7XvnnDAp8dXw2U238pi2Yl8euMabvKP8JIAHNl8AOlqt8fP7r2T9+/50vNk3c5BXvgsjj6vi2ff+DPZkaK0ic0EVnlJGADHcaaWZsm35Z/Lx84KC87b3bxt0o53ubefqbiyp/e0vL+GIqHMZM7nDBtmKcbTpBruqabsFDFZApzJXMOK90tKwlRkeh6p5J7XyXlrA1obHjl8iLn2Crt7S3h+Czdq0dUdxPHRnocxHtpoWnMhSvUZbayjVA9PeSzOL9BpBywsdunOtQhaLvNzDsePPc5jjz5UrE3aytYb7bVTcYkk9OZjoihdo3QQJ7iex/x8m8XlRZb37KXX9mkHbZLxmONHT9DfGHLTNfOsD4asrG/gywbJCCI9pjM3z9U3PIW5+Xkc32OsY1pzXXbv38uxY0fQccxV196AFkUkLgtuB6UUrVbAow/eR3/9FCY2ROMhOh4SLx8g8No4EaytrbNy8gThYIM4HhGrEcMoJtYJ4jgoJVPPaXW5FinfBiYCsvZUZfOZp593A0aD1qQe88ndl/y+UywGVHqmFCKTtVNFBIU0JESyWCyW7fPPHvgWvvjZq1D2JWKxXHD+9CPP50+WnsXtX/4rLEj7QpuzMxGh85+PcMsNHySQzoW2ZseyQ0TpbLF2JkmJtnss5HMfs7bNZF5kfW5rU91FIpj0FEq/BFHT82Prn5uERJG5NlN1mwXNlttOJYFQ0QX5tTHpHMB8f3neYZF4pnT9K45fKS0Tko+AZeIl95qphpGxQvzIZEvmeCUP+ZTMw6YERqMht3/mU1x97c1cda0PyTqu6xL4XXSwQOK0SWKFxqHVdojCiDCKWV8/hRFwPA8dQziMOTo8yfFjxzh27BhxGOEood1u4wctXN/nwfsfIooTOnNzLO7ehR+0+OynPs/KYJ1DJub6p/RJoojYV7iBx/LePYhStNfXGYWH6CnBDzrMz6WJkpTj0Om02VhfJZj3aWHw222Wdy1y9XVXsrivy/4rrqK9uJuDoljYvZeTR4+TxDFGx2zsuQLldTl54gncVgdXaaLxKjocoAcOSWxot3qsrJwiSRLCZMzaoE9/NMLvLqKUixKDmDSTbeUZkfTHyR5sUTK5f+TPe7ZNJoHbk8RFBiQp6src46jMq5mG8qop/2c+z9TkX6h8nymHt2cL2Zh8MZrykjS2t2m5+DFDh++6/xt5/d7P8L0LR6b2zymfx/5ZjLzyZVz587fYSIFtkhhlw/8tlp2CBqOt928rfCexSe+2YGeIUqmKtu14RTdjM+9m5fjNJtVtUX/+WyauopmC+nTnx0o+H7MSzjgdmJlnM82LFMKUkljPQiZzkZCXm9gybdtEPOaiPU9zU9pmTJF/QqQ2OFDePnWR8zmIpjgnUYrxaMzDD3wRz+uye9c+4sEqnqvw2/MkPU3ScjCJIOIQtFx0lGDiiI2NVRzPp+cvohNDEsWs9k9w/PhxTp44ju8YfN8laAUErTaOF7B66iRxnDC/uMTy0jKLi8t8+pa7CAcbHAuHDPoDdByT6DQseHF5GdB4vuLYscdwPUVPecwvzhO0WnQ6c7Q6LTY21pkbzeG6Dq1Oh8WlBa685grGLLO0ez9eb4FFP6A3v4RJHMbDAaNBn87cMuNEcejRB5kbDUHHhKM1MIpwo4XveLSCdPQxSTSRidgY9Dm1vsHu1gKeKo2IlJ5lESlEqaF82U0xDTR9hKQmZvO5xGVhWlSa/Zl7VcvPRm2QBUPqdS/f/nReah66nXtZK89H5bfFcvGiRoq7Pn0t6ktMoygNxOPul/0eb7nySzn8CwqMTfwBoObmiDvO1gUtFstFSeIbnPl5kvV1OxhnKXjSolREHOCTwCFjzNeJyHXAu4FdwKeA7zLGhE+2nS1saNxWWfLkAjz0m3lYZ5UvltA4h/aW28ltmpmAaRMN3ZThdcvrbTLFK1LE/OoknaM5NzfP4cOPcXJllZe+8JnMtTyOn3wAOhvQPk537/Uor40hJmGdMBxy/OhRgnYHPwjQrgITMRoM6a+tsnLyGHv3LuK4LuE45PEjT3Di5CnabZdeb4lrrthLdy7AVSHdDgR+wO69SwQLbXRLoVoebc+h6weMRkPGYcT1N97MqVOnOHrsCVptn4X5eQ5edR2jCAYxeF4L12sR47Ln4JUs7b+C3q5lEvFZGWh+/31/xK233crR46eIohgdJuyab7PU83npzXtJwiG3fvTv2LdvH91Oj/neMmHk0E8cRuN1onhALBG+7zM3t1AJRc/vwZSHPhegmlyFTt3W8nF5RPgkmZeaOdBTf5YrYe9Nz07mjc2dp/Ws07OWTdoJ7IR3ncVyqSOez8p79/JjN76zcT6p5dxj33WWc83vvOmX+eOvex6f+babSO69/0KbY9khnI2Udj8E3FP6+xeA/2qMuRE4BXzvWWhjS8pCq8kreS47ubPqnmXPVvNU6x31s2Vj6a/K70aPbvEz67pNb9/8+pbcr1CL5pwIkTiJGI8H6CQVq9FoQDJax4zW0wOUg1EeolwcpUjCCJMkeK6DThKiKEIwuK6iFXgYo4njiDgMSeIYrROUEhwFmIQgcOn1OnTnWrQ7ATgTz2Iahq3SZEqej+cHdHrzdHo9Op0ugmCMxnE9/FabdqdHog1xolGejxu0CNpd2p15RsOY2z75Se75/Od5+OGHOXHyOMdOnODRI8c4/MRxjp9cpd0K8FxFHI5Ba4xO2OifYDReI9YjkATlgOMqXM/D93ykyCI9uQdNP7PCApq/I/lx5WelzPSzmXvLy89G1befP1d1ey4qdsS7znLxcXhjnnevL3E8aV6h76ndI6x92wtxnnbTebZsB6KEV+6/nzd0Ny60JZcz9l1nOT0ixbvWbuQz21zi6iUth+9ZvgXj23DWMonR/OmgxV+tPvWyDBh7UqJURK4Evhb4n9nfArwGeF9W5HeANzyZNk7Tnh3nXTldtNZorc+6IE3XiiyLge0J5NmVNg8ENK0TuxXaGBKjCZMY13fozbUARRJp4lEfRus44Wo299DBSIAftGm326A1vuOwODeHTiJGoyGu67KwMM+VVx4giSM21tYY9Af4nsfevXtQyhBFQ9ZWT9DptLjy6qs4cMV+FpZ6jMcD4ihGx+ncR5MYojjBC9q0ewu0ewssLe/h4BVXopOEjY0NRlFMqzvH/iuvZjAK2eiP8LsLiNciQTEaaD732c/zr3/ix/n43/414dop9i8GLPU8kiTmxKkNjh5fp91qMd/rsrwwx/LCMt1Wm0cOfYGV1SMgIa5v8FuKbrdNp9Om1W7hOC4iTp4Wq7jf1Xu/zZDxyt+wnWekLESnn68pf2z2v8lrp/787FR22rvOcnFx4t5d/MSHvo1bx7sa9//Yri9yy39+Ow99857zbJnFUsW+6yxngtpw+E8f+np++pFvuNCmXNQMTcg/+eh38Bcfec6FNuWC8GTDd98G/EtgLvt7F7BijImzvx8Drmg6UETeCrwVYL7t1/cVn7dKODSr/GZzVCv7KNdPKTvo7BDa6TmYs+eS5n83dbxn2bVpOO027Cm3X79+TW1Kg82z2igLTq3T5El1W2d7jlNhXBY8IoI4gotiYWkZwRCNxwzHQ5TvgHiIF+AGAToeZ0ub5nNnFYHrY2LN2qlT6ZIx4vHYY4cxyQjXEUQLSWxY72+wuHs3i7v2cPK4R6fT4anPfh5XXH8Du/Yd4NVf83WsnDjO4Yfu48DBK+l05hkPY0hiTBSy2h/SHwzwXRflt5ibX8SYmCTRHDt6lMi4iN/B8Vs4rS5j4+D4HZCId77znTzy2GM8/RnXo+IIF80VuwMSLTzjmr08eGgDY1xC5omTFUbRkCOHnwCE8Shi1B4zjoZ0ex0iHXNiYw2DwvUcwiwkV4nCGD31rOksqZEU91eRTgaeTrI1uU/F1qn7n6KYHsIre1nLddYSZ2Uf8+RG5aiA05l3fQF4G2fhXecsLZ1bKy07FtnO2N+OfPTPH6tvegmrb+jzc4u/AdjQ3QvE27DvOovFcgE4Y1EqIl8HHDXGfEpEXnW6xxtj3gG8A+DAUq/yn+smAZRvnzXnrEm8zpoDp5QqJeXJAzVroap5dt1aUqOmkNWtOtGbicYmO7fbKT+dznt+LlNeNMjCUBtE6YyQ5NzmreYYVkVw7q2tedcyG5QLXs8jGgyIxiOiJCLS4CoXcT3E9UljemOUKJKs3nbQQokw6g9oLQQ4rrC+fgrPMXTbLkYbklgTqwQvaLG0aw9hHNHpdlnaewXB3DKqNceNz3gWGysnCTxY2rWXoNVjsLaKjg0mSRiGEcMwxvUDHM/DUwZ/1CYMQ9bW1vC7C/SikNbcHI7fJhEXVymINbfd+nFW1lc5cN0VmPEYN4k5uAtcx0OcDsPQZbVvGMUtjPEQVzh1apU4NsQqJhyHjMMRCwsLiHZIVgwoB8d1MWEpq9Qk1W2VXJjmc0k3+X5kxSu3f+o5E6Ah017hAS1VmyfbkjyxkVCa1ypTUQGbfXcvFGfzXRdcfdXOOTHLeedYPM+p5CRLjl0SoIkTzxK++PL/xSxBGpmEU3rEON4ZORovNc7qu+4q+667HBklLkeTPkuqhSebJyvzMES7O/i7lklOnDxPFlp2Mk/mzf5y4BtE5GuAFjAP/BKwKCJuNqp2JXDoTBsoi5pc/G2ns1oXq2VBVg81VaIw2XIa+Rw4JYIpHdPkzSnbNMvu7Xawy+dV9jqebse84iErdfbTbWkW1Oq2GSKmVie144wxRdbcek7gJq9pei0U5fVPJzbkQZ3p73AUMlhZQ1xwOwGe2k3iLzByuuwOPDzXw1XCE8eHDAYDXvT857Mx6PPEyaM88fhh+qNVjA5xAxffd1k5tU4Yxtz8vKdy8Opr2X/1NRy49nqOnTjJb777/bQXlugt7eK1r/oy9uya42kveSFGfEQcdi8vEw/WGZ04wtz8Io7fYXlpkY2V45x6/BgJCuP6xKMBGI2nYHH3boK5RVpLe1g5cpiTjx/mxqv38uDjMZ/4whcYjAOMcXnBSLNvIeCaPZqleQ+Uy+fuO87Tb1ziNV/9lbz/dz7Eow8dxusIw4FmOAx5SruF4wV4XgfxPIzjMoyHxfq8ufjbjHQOb7rWaHk93/JzU7l/Tc+DaXhqCsU5OdIYjdYGx8lCx42mGuZrKomRyr+3+10/T5zzd53lMsDAz/z1G/gv+9f51At/b8sOm2WaPxvM8UN/8/3IyLncncrnCvuuszwp7r37Sl78wA/xP1/9W3x5e/Ns4le7Hf7tb/4m3/+p7+Lqb7Gi1PIkRKkx5l8B/wogG1H758aYN4nI7wNvJM3U9mbgj56MgVXPXdZZzZYVmdVlTTu0eR85F17TYsjki1kYKfWnJf8/eQhvKvYyT1Ph7Uv3i8zqQJfby/8ue0ynO+Fl6p30pjJ5OxXba2XLXsmmuZ557UpmyRlDYxrV3DMn6WeTpVM1lVry0M3MW1YT8fk1zr2liICjEM8hDCOiMMFzXUZhhEnWmZsfgJ8gnkfgueh2izgM0cR4vkJEZ0sqaKIwpK8TtDG4vs/Srn2MYnjwkSOsD0ccP3mK+x85QquzRrt3gk6rw66leQ7u63HlFVexvLTM/Pw8+Akm6OH6G3ixJtEGYwRRLnE4JE5iRBSOo3Bdh/E4BD+ihcPRo0d54N7P0+k6tLs+a4OQ629+Hrv3XMn6Q39LaxiTRCM818f3DGvrp4jMAr2lvSzv3c3aSp/Dx47jtxKWEMbhGNcYHNcBxwHHxZH6c1YbFCiH4FJ99qq3Mx9sEMpB7SY/prZSy/QzP51sSZEO7pQPNFSPSQdKqJTZaZyvd53l0kcNFYNBgEYD06LUPHudk3//pex5/90kK6vn38ALhLN7F0ff8BTmn3GicX9iNO9c38uHTjwLtW69pOcK+66zPFkkFCR2GRkP2FyUOqJ4ZQuuXF45L7ZZdj7n4u3+Y8C7ReRngduB3zidg7ecNyqTMNCCBmE37R00QN0LlAu3UlVA3rHPhagxubdnUne1LdPYSa/bPx36qqe8qbPm+c1mInbLZ1H1CkuR5baOKZtaEoepxjSFnpeJUi9EPwpMLnsy4Z0YKV1XqVzculAue0gla9Np+fimS399hINHa9cS6yurDAZj2p05Op0e3XaX+bkO8+0Wd9x5J0Y07a5Pe+gSJQ5ioL/R5+RgA5TQnV/kwJU38dkvPMAnP/dZ7vziFxkMR4CDLxpPDJ/8xGcJfI+lhQ7f+c1v4KUvegH+3G6Mp4i7CW5rBT8aM+iPSBIhaM+xtrZKGI4JOm1838cPAk6dOIU3MnT3Xc89d9/DR//y//LMZ+xmftRhfWD42jd8O698zVfzo//g62H9CcL5dXw1T8sTnjjxGKNoH97CPm5+5tPwvIBPvvdR2nOLeEGPjY01PN/DCeZTUaocPAWi83uppsYPlK6GWYvKA2mnBzumBGv+TObPxUzxOPF2lr8XSklRp8lCdqvh3FL6blbr3UFe0s14Uu86i6XOPS//X9z7oj4/dNv3wmUkSpMbr+CDP/WL7HW6jfuHJuSnb/0G5KSdZ3qBsO86i8VyzjkrotQY89fAX2efHwBe9CTqAmaIU1PyrmUbyn3aWVlfJ8Iv7SDXQxSny6dtlEN+t5twKU/uopTasp1y+OzpzqWrzMusbZthXnUubbn8djxUtTrLXrnKPTN1D+0ErXUlvFdysVuqw/V9lFIcO3GC8XjM0nwXF02gDE888iBBq8PCwm4W57r4rkuv12W93+fIkWMMwjUSPaLTDkiiEf0oYa43j+v73H7Hndz5wGHueuAQvgu79s/zlBv2g07QOmZtaBgOx6yeWOfOz9/POHH5+t27mVtYYGnXAaKVE5gwRpQQxgmxcei05/C8ABwhjhL6axskbhvXGIhh2O+zevI445GP0SPavs8Xv3gfKriF/iikAyid0GkF4LUZD6A7N4ffXaS3vMz88knm5mA0WuOhhx/lwN4enU6b7ryH+CDuxDs5+74JStK5m5KH98561krJkEQmns3CuznlZM3vcZ7Aqrr8UZNp9Xna5WehLFR3qig9m+86i8Vi2anYd53ljDHwL+/4Zn5r7xO86/o/33Kqwk9e+6f8qz/7Rvxf3UXrA7edJyPPHxvf+hL0W47xMwfeS1OEjGXCzoiDMZsLymLeW7ohDQsssorODvqbngOaz6nbasmSmkevoRM/OX46HHHaczmxp35es2j0ajbMaZ32yDaFAlM7pvw5D23e7HpMDwZM/q3ZUhKalbm9W7aQ4jguynEYrG2glDAejTA6Rommv75KNA7xVEDLNRAEeJ6HAMPBgLEeEOshjkpT7pjE0AoCcFwOHTrMkaPHObm6wU1XdNi3u8N1V8wxGMcMxjGqFeN7Qtjvc/TEcXBarJ06SavVYmF5H37QIQraRNEYEMQIQauNqz2iJMZow3g4Im65eHGMjhMcFJ7rYnSMI4a5TptjTxwB9x4w4HoujkpQIrjisLy8yNzcHI4b4LfatDot2m1FkoxZWVllvusgIrj+CGUclHGKQZDy4MaU2DP1AQsphGZFJJaPKc373FQemurapuX7Xtawm0UETEiPOJ354xbLxYZJhPuimINOZBMebYNTyYCHYwejt5oxb7FYdgQGRg/PcfvA596rQg46ZtN33avamlue8wc87Xn/kOvuuY7kgUfSxJaXCCs3KO56zh9gBenW7AxRuh2y/qki7TTrusCrFzfTMmhWJ7dp/mVTGck8TrU9tfJV0XcmyYq2snUzT61U4ywrdZbrnZyzQopVLmfUm1dZ0qSFjKnbUmR6rYnlJlsatotS6cCD7zGKQ75w/73MdTt0Wy0WevO4joejQ6LxCIwmDMeIEzO/2OKJh46xtnaCtquIxxG+69Np+YTacOTRQ+hBzL65gDe+5kuYa8P9D32eTzw85u4nIq7b5XLlvnm+5utfwCc++SB33/MJPnLLPp7ytGfygoX9zC/uouUI933xNpwkpqOE3bv2IA6s91dxBMKNNfobA8IwZmPvEzzv2c/lmoN7Ofzw36LcDb7sRXPcdd8n+dwn/o4vefpeDnZ7LHRD7r9/jX4y5s1v+j727N1FEo5xgJbvsmtvj9FgTBSOUJ5LIsLR40fx2gt4rdRTm3qfDZWpn5tldG7wUBf3qBioMOWtkxtWLm1yMeoUz131/s5+9pvmUNcjFCyWS5ITAV/3Zz/E177gDn75ilsvtDU7nh859Dr++vanocZPall1i8VyvjnNd93/+77/yJ/8vZv5wOueR/zoY+fBQMtOY0eK0ilBkwuWekc7+90kguqUPUqbld1MmDYvC9MgEk0a8riVTbP21zP3bs/eqjdsOgx6i86+YWLzJEtUtf6SR63JC5a303QexXzVsp1NHuks/NfNPIz9cIg46dqxLa8FBpLQ4PkBSglhNGI03qA/OMXGxhr9QZ+lPXtJlIuDojfXIUwErzVHR0IIElo+KAcGtBjpGC3wytd9Lbt6gho9zL5dc3jG464vPoS0Frn5mRv0dIQ2mjiJMHFEpGBjI0aTsLp+CldcPOUh3SUkiXCciEcfe4y7P3cXPWdAoiO6zpiO9OmYPm7o4XW7tHuLxGZAlDjsO3iQduAyWlvhxOOHOHHkCK7fxosNYkbESQyRIozBRXAct+F5nRaC2xd4UruxpnSfTGlTOowx7SE93fZqbQNl+60wtVySGFAjRT9pnh+5qOC+71xiz+0vYe49Hz/Pxp1/Vt/0Eo5/CXRmhPj1Yx81soLUYrno0Glyt1nvujpXuj2e3jrEB5znn2PDLDuVnSFKZbYHcCJqKPIU1cMNm8pPe4rSSpq8hqdlak1Q5R6jsulpYpiJR/V02pn2ZDaL41llJudZsbrihaqeS+rPysOjdba9OLyc92YLjSDVf2aXK4V3qlrSKpMlV/K8gDiGjdGIGM0ojpgLWjgmJB5C0F7EcRXj8YCN/klOnDzEqVPHGY3HzN+wSBJFjJw+y8vzhMalvRAh0ZBeMgIzZhwr1tQCkUpodQzf90M/jhke4Q9+/Se5/qp9XL2seOf/+yxjOrz8FadQfghRiDYJOgmRKGZ1vc84HHFy9RiB49N2A3ZfGeAQEXgRn/r07bzvvX/K6199E915aHmr7Ar6SGeM2jiE0ztAd/EmtDpFjMP+K68m7p/iyAMP8MgXPs/jhw7jBD0CY/AlYhyNCY0hMQ5d5RAELZIkKe57k2dSqH+v8gzJm3kxy3c0m7edP/GSxwYoCskqm9e32TNQbdNk4yFWjFouX/Y6Xb743b/GV7zw6+G9Up1/cakhwrX/8F4+ft1fkq5AYrFYLnsu4z5AskNXIThf7AxRugmVtUKLBUek0D3FMhSNR+vankmnt5wFlCwx0XbElKkps0zSTRLIlDoQWyc6ambr8MV83UdBVL3ctFBtWnJjysMmZpJFN4vedJTDROpMf1FUaU5rXpsuliSZCJryfFNKgrQpXLgIPzYG5Th0OkvocEw0HhMrgyhBiSJkgBkb+oNVTp54gocfvJdR3xBFLrd+7C7abY+5XovnvvSlSNCGu4/jeS4tp8UwConHMaP+CaI4ZBwqfvt338V8MCY0Hgu+R9sIbqvNyonjfOIvPsirX/lidi31MOGA0cY668M+J04eJ4kjFubnSMYJKxtrrEf30g8HPPuFL2DRU+wOXO65+2EWl9pce9NuloIEf8HgKU27vYulA0/ju7/rZThui5P338ljD97PXbd/kvvuvY8oirn+Gc9luH6c9VOK9eEYHE1nYQ+OozAmxpiEXBhq9CSsPb81U89r873cDDVVPPeQVmvdDk1h8PnzYUxSmictp2umxXJJ8fPX/wG/8HdfzeG33Uj3fZdfmO+nxiF//443s3aii/WTWiyXB8/xh+x/1wn+7i9fynU/ccuFNue88lPHnsH77nsurHkX2pQLxo4RpbMy3Na9jGmoLhRev6nIWVMqWRZ4s3q4k07w1nNApSbBcjSTjDKk4bvbGN3Ol8OY5Q2d9oBmbZtSx30TW0u1leqZccxUCHL+Kw/nbWqh7nlusqGSZalybLX5iazN76sguG5AFEWYxBCbBEdcXFcRJSOScUwYjRiPh2xsrDEKO0ShYuPUCouLHfzAI2h38efmmVvoMhwZ4iTGGI3WMUk0JEkSwlhxxx13sG/R4eoFQQkoRZpwqd/n0fu+SPjCZ+PsWkDHY8LxgFF/g+FggDaaRTOPTjRRGNGPTxJ02mysnETikI4rjPohSbfD8vx+/FaXUTwErdm99yDzS/vYs+cgnuPy4Gc+yuMPP8Chhx/m1MoKyvGZ6/Yg6jN0XbQeAhrX8xGlMEaTzyXNb4ApBkgqgdRMRnHyXzPmLNfu3cx5xrOeTU4vMqCcMCz3yGZP1mU9Wmq59Dk26vGZ8Zin+YpApjshzw983nv9h3nugZtpXijl0uZE0mX94QXUmY3tWiyWHcJW77oyC6rNb1z9EZ71tKvPk3U7h3vW9zN6eG4L99ilzY4RpXXq8yrPFpuFxZ5RfWllT6qO007sInVBODtT7xmHKIsQ66T4e1oCz7K36p2uJ8ApliU5DRzPxSjNcDjGBMJcJ2B15RjheAxo4iREK5fHT2ywvqHxEXrKozM/T4TQDgK+9OUv4o47Psvn7ryT9o0HCDC4yZh4PGZ9PeLWj/0/brxqkae++nqi4YCob9Am4dSJE9z+xCN8xZe/kr27F+j311lfX6G/ukKn28FxXEZRiDEa5TqMVlc5Ej7In//RH3DkwYdZbDksLS9z09Nu5o1v/A5MpwOBj6vGuI6H73Y5+ujDPP74Yf72wx/k5LFTnDi2ytraCL8tGBUTxSMGgwEiCsfzaQUtXCf96laW2AFU5erWB2NM6Wcz8gGW5sGcpnnMp0t9eaI8WiHfdClHLFosAHffcQ3f+Pl/wnte9yu8KLjQ1lgsFsu54e47ruEb7/knvOer7LvOsjk7VpSW2c5yEnUvay7IZonQavjqtPhtXP7FGKC+1mc9VPb0vUTFkjeNGUnzMvX2thYDW9lS3Z953CTLZFw412RGU9Pe4DzhVDWkOfeKGiSbP2oaPHBTdWV/K6VIELQRxlFMkgwJR2NEJ2BS72ScJDh+QKISIoGW69Bqt5if7+K3WnQ6Ha6/psv9997LxtoG41DjOoaeirlqycMNAlwTsuyG6I0+KydjBisx7WiMxBEqTjh66BDdQLG2ssKg32c8DhHl4Loaz/PQiSaOo9RjOgo5ceQoGyurRKMxLReIhzz68MPsv+EG5ubn6Z9cZTBaJRo+yqH7v8jJo0cgjlGSJjDavWcX7V6Pli/4gYvfahGNQhzXTZM8OU7DtZvM9JyE7U68p3kIfJnKdyuP5KYU5rvFHM/6c7udZY5mRUXkLZ9h1LvFclEhGogEbTYPTvVed5xH51/Gtf/9cyRra+fHOIvFYjlLSMK23nWXK4/EG/zHJ76czx05cKFNueDsCFFadEm3ma12M1FaTpi0neVVtg6DrXb6m0puJmY366Q32bftJWEMU8c8WUymRssh0pt5Yxvn6KpMguYhuEVYc0nYZ8K1KYQ3F+jVc1MkRhhHCcN4TDTsszDXIvBdxsMhSRzheAHaiUgccH2fdqfFwmKXoN2i0+tycHGJj3db9DcGDEcxnSBhwYm5Yfc8B5wOg9UTzLUS4tU+K0f6rJ0c0wsNomM8A0ceeRQdDlg5eYJwPCYOQ0DwvATXdYmShDCK0LEh0REnjxxlY2WNaDCi5WqS8Qb33n0XvT27Wdyzm9Ujp+ifOs7q0cd45Av3sHrqJI7v4bkejueyZ+8+5ubnaPlCK/BptTuMY4PjuPhBq1irt3L9Sv9OrrPO79TskN3ac1qZbp0W2PK5365Xvnx/pz2uUjyDFstlgYEQh8RoHGnusH3iS97LR5+u+bn3vhE2+pfU+n0Wi8XShIhBPB8TRxd16JR4Pltp8c+HS/zZR58HdkB+Z4jSOqezlEp5mZbTFWf5MjFbHTbbswPluavN9W9N/Xy29jblgm52eOUs7+v2mMxBNJm4qdeStjF9DrkIUmoiZrXWKAGc5pT/1UEEmXr/+K2AoB3gOQ5xNCbRQ0KTEI0jDj9+iFGiQRRGKcRReMow3ljl8YceYPXo8+i25plrBbzsZS9k35VX84E/eDfKjHnNy1/J2sYaG8M+zoE9RIlmfTTmVV/xBg4sH+R3f+N/sHFqAzNyOPzQQ5w6/jjjKGY0jBlsRMRdFz8QUJrBYMxGf4ON1QFGG1quR6szx1XX7WJlZZ0kOclc7wRrD93HqWSDR+++kzgc4OgxJ04d4+ixUyTuPKNwRD8ccLANva6DhDEOiqDVoWMUOB6x1rhKoWYNppRjYOtThTcb0KltV6JAzMxOcD0aYboNU9LI23muLZbLC0mEt3zsLdx08Cgfeuqfziz3HD/kxe/7PL/74Vdy449c+svEWCyWy5vffc5v885bX8JtP/VCWh+47UKbc0a4115N9/f6/H97f+9Cm3LRsCNEaaO/Jw8dreytd35nT+fcfie3eRmKxvDfalwrJv9YaUqKOvPtoqYHeibJl6SUtLfZG1k9pmRn2SlWmQdYCsCsVznTw6oqO6dCLWVyeOM1LzRoHu7bUKi4YbMT6JDVXzRpDKIU4qTnpRyHoNUiiUKiMGI4HhMZQbutVKaLwXMVURhx6tQaqydOMDc3x+Jim6X5BW6+eZ5b9l0JesyBq55Cd+0Y/Y0VvGCeSAsro5grrr6OA4t7mGt7JH1FFAthGMJAE5mEcJwwHsZARBQLbpAwGicMxwn9UYJJNIkjzM8JQctjGEu6xmkYsnriGJ6K6K+dIInGuBLTH47oj0IkSDCSekYD38H3FBhwHZdWq80oBqMcVD7HV6afczGluyjZ/Zj6DjV79ks3iuJZqhxaHYwx+cMw1URpEKcaIV78mVctebg4ZU+vFaiWy4hjAferPfzfqz2e7p/iSrc3VaSnWvzUnrt533XPPf/2WSwWy5PFCB8b3IQnn+f5wdbrlj43CHju/tt58dJLLtrFokw74KeufA/P8NsX2pSLhh0hSlO2E2uel2maf3imnsH82Kq3tUmoVjPrZuIvW6M0zVKb25PXkWVHZSK08sQ0pqJoyyHHuVcpbohYcKrhtMYADpQzleZq2JREpmnyCueqoOmaxEwSFqXhs+X0RcV8w0KP5N5qhZjS0jpFRK+TZrTFZIvZlIVHzQtdzG3NqzAk2mA0hPGItu9ycO9BHnjgEY4fG5CIoLVLOHJRSUwgMd25eQbDEccfWGPvZz7FxspROv4rWNi7j6v27OXHf/LHMJIuabOxscpw0MfzAzpzi+y98kb6hx9g5dBDtNs+424AJASdFo7ncvLYBqP+kOHGgBOnxmnYsOowjhIGI8PGWBOHmvU4QakBLS9m9+4OrVYHLXDv57/AfV+IWJhvE4Vj1lZXOXGyz3o/YamnWZqbY/fiQeZ6XXzHQ1yPTs/Da80xTE6SGGh5PgaNMUkRKm20SZMcZSJPV4J184spYEqZohvRFe8mGJhadqga4qvzx8lMHqt8jEWyDRPnrckez2yQIQ9ZLB9ssVxm6Cda/MCffi/f8sqP8wv7PnOhzbFYLJaziiTwK3/xlfzm1S/ljhf/r5nTFSyXNztIlE6HxaYCbVO3HGfPs1L1Js1apqXwAprcjkzsZX+m6y9KrY7NPFOzRLQgUp57V59/V662Wn9TQqhJSG/+9/RpT5IUNZMHeUqpfNOSMNJQb93k2WMHkrqWSxXmLUZxwkBrjq+ss7K2wXq/DyZhOIpZWx8ROILfaeG6DqEIYWJ49NBxxlFC0PJZ3L2X+d176C7sIuh0WFxeout5zC0tpR5ZDBvHjxCur5CEI+bm5hkNYtZXV9ExOI7CEZ8kDtnoJ/RFgUnwVgfoJCZODCdDGMcGnYyZ14IrDovzHbyghaNitI7QOmIwUAz6A44fW2EwiNBa0e60abUCXNfFcdIBiCiKCGPNONJZciOpXCtTvqGZEmwI6K7cwZlItXR1R80jm3tIp44XKorVVJ9hMZlcrgwAVcOHhc2fQ4vlUkQ06Mb/3k14y00f57//6mt5ym8P4bY7z5NlFovFchbQ0D/Z5tsf/ArevP+jfG1ntOUh7nc8wUM3v5Trf+4O9GBwHoy0XEh2jCitCpyqC6/iBKxxuvPUtvKkmgahN2VfJYa1WRRXhWRVNG42/zXdn9Y7sUU1l6+ovybv8ZNlcg4Tz7EUUbgikwVINkuiU4gPmXhBq37ikt0N55lvShJNFCUMxyPW+n36wwG+lzAeR6ytjOjMd/GDAM91ECXEBg4/cYqNwQDPGbK4vMzi8i727L+ehcVlWo6wuLRIr9MjGo8ZhyNWVleRwSrJeES302MtGKKTFUxiMAmIuMSJYjA0rHsGQ4KzPko9wAZWI2GYQKQjrtYuYhLm5tq4nkcUJyRGkxjDaBiysTHk5Ml1wrGAeHTaHVpBkAnSVJjHUcQ4jBmEMaI8nKmlVNL7VDg/C5GaXlkDzV8cGp6RepTvDOoZoacPrpZtnI/d9B2wOtRymTPWLgMd0lHN4W0/svwAP/KGd/Dij/8gixfnNKtt44jGeBp0+h8MiU83Cspisew01JrLp267iWtedZKv7dy+ZfmPPvv9vPu6JX73v34JWFF6ybNjRGmVvMOaBwI2h+3WacrquVnZ5iVYJjaUycNutdaISsN2jZkWnWm5XFBWvUnbWSO17hXNvZu5vUrVvZOZZ7Yc/vukM3jlnl5VfE4bK+8nDRGuXa+ZS72IIKhMdE6y7yqohIdWpyYqlKPQSYLRGr/dYxSGrKyuMooVMR7hKGY4MsRj8GJDt2VYWugiShhFCWsbI/qDGDHCwvwGC/OHOXnkKIHf4u5P+uzatczCwhza6ExAuywvLuA6Dv1+H8fRHLxqgfFog/7GCqvrIWvjMRvAhlGIdlhMXDzHpeU67PMN4yhiMFT0VzT3x31ufBr02h7zvgemg040J1fWCNo+nYUe3lwL129zzdVXEYVDNlZOEochjusR9ObZGAw5vtpncfc+XM9Pn0FJPcpVn6LOg9GzaNiq5E+XhKEI8W7+vlSfv7zeJpU6fXz1b8nayr33SqlikMKUkpNprbdMhGSxXA584NPP5UPzT+PPX/qrXOdNzy29nHhpMOR9X/3LJAgDHfCWv/n7qNUd2mWxWCwWy5Nmx73hq2sW5r+3F354tpZGaaLs4WwOKW6ypRzDWvyzTfKQYNlCbJvMa5nbOWm/vlTNrOtTWZoj/1fysOQmkVK/R7Wg0lpYZmFDIbhLQql04NQcSCbXWgDlKBzHwXU9jChiLUQRRIkACqM1RmtcV9FqeczNtxkNxiRxQn8YAzFxBJ7y8T0PQYjHQ4Ybc4DGcVxarRZ6PEBEkcRjfF/R682zuqJBNFoMETAShec4+J7HUrvFXBDQDXy6A8NgNOaJ8QCRmNAIQadHu9vGEc3a2oDhcEQURyDg///s/XnYLUle14t+fhGRwxreaY9Ve9fYVdUD3dBNMzTdjYg0qHAU0Auo9yCDeIAD4nSuD3oOV44+PF696lGPA54WBzgPMspVFAQEBWya7qbnoXqo6hq6xj2+wxpziIj7R2aulbmGd797qNpvVeW3nrXftTIjIyMjI7PiG9/f0O0QqT5B2EUpwVtLmiaoSKEr92CK++oXeola36zqxTkBbXayny32NFEzRJ/fGGlsXTxFJaEv1Sfz6F1LWJcz2NejNL2Az3KLFscVaqTJ0w4/e/CFfHnv07w9Xu13deXzofN1X0L8ax/C5/mL3MoXB10V8kVR8X3sptx39yWeinfwF16qYU9atGjRosVhOBakVJZ8OCv/OIWqJqylsnYUM1G4VearczTq874kS9c6x41OrKW81pLClWa6c+K5aLJ7bT/V6yPsy+SxHohq3teH19m4J6Xq6meq7nyhoWneOTcJdoBzHilNhxWeODCc3N7iyoVdklQYT8BmCkxManOSLEHEsrER0N3cIR0NGQ9yJknhe3r1ao53mjg0BBrSNGUwGOK9JQpDdna2ePSRzzAajeh0OuzsbHHX3ee5cilid3/AM8OLpBPHgc65P4450+vyxvOnOLm9wYmtPgf7u1zeG/LeybO42GP6hrPnX8Vm1zA8uMjjn3iEp556lrvP34GJIja2T9DZOIkxMcODAaPBPsODAf07NojjGDwYHRB3u3jnsNYS6rIfZ/eKFd/XY5ZWqHZ/Cl9oiuADDXvqst7V6yHFPl+qtuJn9cwKlPe2sjSo+6IuqqNerSeyLVq8UiCZ8M5ffwc/++AX8oEv+tmVZR79H3+Un/z6k/zk29+EvXzlRW7hi4+uCvlvr/8P/OTgJH/9l7/5djenRYsWLVq8ADge4a9K0kUZN3QWAVQqM0OL925mEiuo4iOqNABdVgXr3+e/pTSFlaXv9U9lLluH9740MywUM1HFX8QtnadQLisFU0A09a6uyi5Oymf5VuvfZx9VtNXL/NpFo0Qj6MKU1qvyPMWsv24uubbra6pms58E73ytL3ztmphf20LfFeecf0qNc7bwUN3q4vYWpEWJzD94BIfCo3EoXJECRdTMfDkwmjvObnPvPWeYZjnTPMcHQnejS2+jT5ZnaKXY6vU4f+4kd99zijOnumxvRXS7hjS3jKYpe8OUK7tTLl4ak2Yeax02m7C5EXLHmS1On9yi34nJpwnbmzucPnWWLM0hd0SiGeYpezaBfoQKcnS+TzIekiRTgm7I677wjXz1N/xRTj34Gnx/k8ee/ByTaYoJInZHYwbTDDExZ++6n3sefC2h6dLrbHLy1B1EvR5OKy7s7TKYTPCu6ANVxjCuxpjHzT7Ff3723OAdeI84hziH8h6Fx4jCiJoVqw3acj1IZk9jtYgwfzL97L9iqcjNns/6eCrG1Pw5aij1nmJsufKZqpaaZs/3qkWRFi1eWbiWRc7b4id5/EfPcfl73voitej2423xk/ypP/A7hHeNbndTWrRo8SLhLfFTr7h33SsVx4OUMp8TF6hIEOWEu1JcSlWm8nmkIj7lUSv80upEa/nv4vflifByAKY5eRZxzLMsHnJtNaK4CqtV3SYpnZ0emZFxJRqZEd7ys5Da5vpNmss+8Ittm/9dV+UswqqohU9lZiozylFVJxSpWbRSaKXKqyiIqVCQqMJ9ck6wtRK2t/ucPr2F9ZB7j1eeMAqJ4ojcWpQI3Sji1MlNTp/eZHszZqMXEscG5z2ZdUwSy2CYsb+fkKaO3Fq8y+nEAZubXTqdiEBrXJrT6/bY2trBmIDABMRBSOIsY5uTG8GTofIhyWRMluWE3Q73PvQgb37rl7F9512o7gb7BwOU0vT6fZwovDIEUYfNk2fYOX0ngQ6JwphebwMxARmwPxqTJDlQENLKfLwYCrVFnIouymyYFP1bRhWuPgrQUkvFshggi9K8t/Y4NI1954R0tmjE8gLLqrrnY4SKsdbEVL/0RLaqaYsW63F/0OeTb/+/ufpl6e1uyouG+4M+P3LmYzx05hIuvungCS1atLhNGNmIy3aEPUIQlJf7u06Lw8UOb9o5z7Ew313GCp8zqcjdHEcx0b0RP9NVx6xK73Kz5zkcC76ALxDW9eFhpLYKCHVjeWGb51BHOX5FGa01URxxz913sXd1nyuXLjOcaJSybJoAby3iYWdnB+8cg3Cf0cgwDvUs3Yr3mtFgymQ85rnnBpw6tcHddz/AaDhhvDfiySc+xelTJ/mCN3weJorY3u7xrd/xHXz8kad51/s/xdXnnsVPJzz8vg/jT2+yfXqT/ct7uGiDN33pW3j9m76QB1/7BoJsj61Qc/qPfwuT8ZQsy+nsbJPljoNhwqXhlN3dxzHhhOF4l4uXLpH7ACcBJtwkiGLCOCYsE05nWVaQS329Cx2Lin5lGr9+pNXLFsWL/LeysI9ZTY0bN9u21o90zfPUBj1q0aLFOvzYq/4dj9zd4Vt//XtQI327m9OiRYvrxH9+/xfwq/3X8Wtf8Y954BUe1O3L4ym//rX/B9//2T/BIx+++3Y357biGCmli+aqSyWWlcPrqPva/p/rjqtPqOvnX92Go7Ttmtcgs39uqu5bFdH0WilsbuQc6+7lXOmr2QmvPF6hlWFrs0+3Gxfm1eVHBPI8YzQaMh2NSadTAq2Iw4BuHLHR79LtxIUaKx4UWAfOK9CGzCqmqSKzwiTJ2d3fx2tDZ2OTc/fcy4OvfR1v/pIv5jWvfR1333UPWWKZDFOGBylJ4kAFnD53nv7WDkHUIbeeNLVMUktuS99NExBGMf2NDaIoQhuD9UX0XFEalAalsN7hvFsik0YbgiAsdOdKuFwRYMrPd89dQKl8tOe/D+vrJprmuIuEtGGOzvqxs/oZb46nlpi2eCVjOIr5p3t385nscFPV1933HFe+662Yu86/SC27/TijezwUTEC174gWLV6KUBOFGwSk/ug05OX6rosk4IGgz2Z47bytL3ccI6V09cCsosjO4uWsmHivw1FJXB2Lk+1VxLQsOfs+b+PNKZtV2oyq3vol3qpzLKIKTFP5nx4Fc1J+/Wpus2+hCrhTKzHzYTzcF1ahTcDpUydIpwlKgUOwKLRWJMmE6XiERghNwJlTO6goJNSKjY0N0jTl4GAXrwQVFb65mBCrA6Z5wCTJCTvbTHPLo088yV2v+Ty2ztzBxt2v4tSrXs8b3x7y0d/9PZ761Gf47cefZjR0PJ+PGaeezdMd7nroIfonT+MkYH8wZe/SLp995HECLIESNh10ehtsbJ1g28UYE/P0sx6UodPfIlSG3MH+MIFcIblB52am8kZRTKcTs5dZrM0b/eKcrffm8nLMLERzs8xshNf6fR5x2pd+o8uk01pbll04U+3ki3UutWWpie1ks8UrG/b5Dv/H8/8Dw6+O+cGTj6wt98uv+WWyv2l5x+X/mc7Tz7yILWzRokWLFw/tu+7lj2NCSmXJNJfaBPdaZOkokWCvffz6341z+GoCP5/Y+5pKtc7cdVV9i0SzqTqtU5eaKuhRz7cON6Y6r0e9XfXrWoyMvL6/qp6VWi/4Vb2BoNnox5w6tck999zBdDJlNM1IXY8oUMSxIp+MsS7nYDhE68J0d5IkWOfZOnmWjlWkTpFPJ6QeHn38abb6p7jj/FnO2A02+13OnT3J1skzpF6TofDaYIKIux64H601H3/wAUZXrvDJg302T53C7JxEOQ9pik0mhGHEyTN3sPnWt6NtVgRyijukmWU0nPDII49x6coem2oT09mg34HL+1eYuinSUYhWs+i11b1NkoQsy8lzi/dFAChKRVWJninHUCjBfhYVV4q0sOU4rjq5UE3Xq/OFuXaT4lYLGnVLhEZgI1gyz14MeFQ2qWxLS0RbtFjEv3r4rfzXU6/hp1/9s+zo7u1uzrHBlgr5obf/J/7jxTfysQ/ef7ub06JFi+uEZIr/50f+DG8/9zj/5Px7b3dzbj2eucB3/M2/zMEfGvHp3/cTt7s1LwnclPmuiGyLyM+LyKdE5JMi8lYROSEi/0VEHin/7hyxtqVPw5y3CpDDMuk6zExw8RzXCgK0TtEp2lDWUQvms86s+LD21M+/MkLumrn5YfWtOt+ySfTqtDnrzSuvTdYXty/dmzXnrqMRjRjBi8KLzMIdrSpbRCEWotDQ73U4eWobpTVp7sis4DFoEyKqSCOUpBm5cyCKJMuwzhN3+8Qbm3Q2twg6XTABo0lG3InZObXFmTtOce78Hdx37/1F8CFl8GIQZdAmYGNnh53Tp+mePEna6XAxd9heH9Xr4a3DpgnZZIxSQqfX44677uH0+bs4dec5NrZ3CKOYJM3Y3dvjypWrWEIk6GHiTTAxmIje1hZRJ17quzy3pGmKc3NmtxRNupCbi36jHgCpNNVdjLx7jftfuwkzArkq6vW1FkXm93o9bsRM/4XErX3XtWhxdOTPdvnMI+d4OIu5bNeb8o5Pacy9rxx/pEgCvmvreb7x7IdwfdsGCbmFaN93LV4MiIWDz27z7ufuu91NeUFgDw448a9+F/PhV7bP7PXgZn1K/xHwK9771wJvBD4J/FXgN7z3DwG/Uf4+YlPKj9x4s9apc0fFYqqWqh7nHM5XnniLn8N954AZpT56mw4ncdc631HadKRWlGVXp5eRpf1a60bZW0EuVumkVXoghaPf73DPvXfT3djAK8OVvYTLuyOu7B0ggSHoxFgUqAAVREwTyzixWEKcifFRF7PR54577uUPfs3X8SVf+iZe/4b7uP/+Ozmxs0EynrK5scPZs+fY2Nqh2+sThiH5NCWZJphuF9/rk25sYE9sY7sdkt1dLn3uCT73yCcZjw8YJxMuD4dcHo25NBzz/KWrXLxylb2Dfe64805e/eqHsDplmI64fDBk6+S9vPp1b+Wbvvn7eeObvhwdmGUzZ4q0QCA4R/nxpGmOtR6tgxnZFKUQdWtdyKtFlRtGRV69X7sQc4xwC991LVpcH9RE8a2/9r1826Orc3QGovm3f/3vceZn9lBx/CK37vbiT208w3v/8D9k577d292UlxPa912LFi1edNzwjFJEtoCvAP4lgPc+9d7vAd8A/HhZ7MeBbzxajfMcmHNTwEbmiJX5Q8vW1P4K8/yY8/yWRzfvLY+bqU3LBPSaNaxRDmWRzK7IkTpTsWb9UKbemO1elSt0qQFFH0iVOqR2QM08dnYu5ttX9u5KYtsU12Yq2UIds+8rLrMoO0v8UpBPaRauyPy83nq5wvZUiSbQhk5oiEJNmueMpykHoylJ5rC2aPDG5iZ3njtPt98njCNMoOn3++xsn0CLQokijjvkWcZkNCYwId3+JptnzhL3+uggxGUZ2WTMdLDPZH+PdDSk1+vS2egS9buIKLLccnBwwGg4ZjJKyDNwToPuoIIuOuxhwg4m6CAmQuuAMIw4e/YOdnZOEEUhRgsuz7jw9Oc42N/HieHsubs4c+d5clcoyM37UgRtEgGlil6rFOUqT+zsnizei8aDtoYd+vWjf2ay7QXxUqSuaYwpKZRvqRLTFElsmgs8xxe3/l3XosX1wRvP+fsu85YTT6wt8+qgx2t7z8MtXnw67ogk4Izu8Yfu+hR3vO4iXh//Fa7jjPZ916JFi9uFm/EpvR+4BPxrEXkj8AHgLwBnvffPlWWeB84erbra/0iqnKTrStaJXjnRrfPrplpYKYtHDY4Es0l8Zf7oqU3qF81TmbV1lc9nM0+qNA8XWayu1naHl3qAp/m5F0miX6izIuG+cHatlatyTJakrmba2byeFX18hCBLM79AKZS5qvtcRT9m1yJQxn91qJIbz/t3cUpV5OWsDq5ftEfQKBxGPL04YBobrhxMSdKc4TinFwZIRxEGilOnT/Pa172WyXTCaDxBGc3mzgk6Gyc5uPgMWI8ozcH+AJuOuO/ee+lvneTM3a/C6gArmslkyHSaMR4lHFx6jun+Pts7W+xPhuxNRoiHdJpw6fIVfGjQcYcsUWgdEXT6GGVRWIyOsE5jDiaIchijeOBVr+LK1T1y/wzWeqbDPT70u0+QerBiePC1b8B7z5NPPUcggtEK8ba8r3a2lqG0wnmPtbZUrRXe2wbf980OXn0/fdXrJcktD19Zulo/qfmLesCr+rMoZSRhatvqvrJS+36scIvfdS1aXB985Pjpz/sJ7jKtGdg6/K2zH+WzJ97NVz/xl5HJ8V7oOuZo33ctWrS4LbgZUmqANwM/4L1/r4j8IxbMObz3XpZCchYQke8GvhtgqxsvEMnl/6Fcb/CedaTqeie8R414e5i/5WHnXF935bsqq0lAvdwRCfehtdRI4c0cL2pBQp2XWPg7/9649+tpTwO+VPWqhQCtNadOnSIIIy4PPscd5+/igfvvZf/C0+TJGGcdzz3zDNl0REcpOhtdEhXgbc5kPKK7uc3UZbzr997PW7/kjbzq3s8nMJrceR5/6nPEvS1M2EGH29jRlOTqgEvPXebq1T0Ge0P2Llzl8pPPMYiusr29zentkwSjKX5/RHf3gF6eo8INxukYm01xacp4lDBNPblXOIFxKuQqJt44wT333gPe8YH3/g6STCHP+NAH3osghBpe89rXc+/9r+L33vcuBoN90nSIUETmVRTBjESKRRHn/OpbsgJa6yXf0Nq6yyG49jism50759b6NB9DUnrL3nV6Z+eFbmuLlwn0nWN+6E2/jBZPLBmndXS7m9TilYEbft+177oWN4LdZ7f4gvf9KX7o836Zb+nvH1o2EM1bfvj3+IVv/kIe+q6H8UnyIrWyxYuBmyGlTwNPe++rkFk/T/HiuiAid3rvnxORO4GLqw723r8TeCfA+RObfhWRLMtdV6OuRSBv1r/xMJK52OajkuDV11o3YfUsiJ7rURdmq03X1YcFKTxaPzVJpSzY9Da218rPoxWvWojwTVPTaywm1Puu2+3ifOHfGoQhvf4GB1cMPlV47xmPRlx2GXeeOokOQqDIZ+rcFGUCbOYYjA5AGcLOBs5mZDZjkiVInuNUDvmE6XhKMp4yGo4ZDcdkSQa5J6AghOIgt47xeArBkOFwgmhFJ4mxWY7NLdk4YTKeMp0m5HmO954kL3Kcdje2OXXmDgSHDiNCgcDl7O3tgvMExhBGId1eH2UCjAnQukeeWWzuZjlIlYA9wq1ft4iz6m5XcZWWA1pxXesZ6+7nMSSkcAvfddE9dx/LC2xxjCDgNnMeOnOFb9u8XNsR3LYmvVQQCQTbUzKJUGN9u5vzUsUNv+8a77q723ddi6NBjRWjx7Z4/IEzcA1SCvB37/gQp4Ihv6lPvwTCURwdZ6Ih/kQG+wFir13+5YgbJqXe++dF5CkReY33/tPAO4CHy8+3A3+7/PsfbklLj4AbIZzLCq1cY//RyeZRz7usxpZkVOYkbr59Ea7Rlpl5bq3uw9LH3AxWBrmpsedmkKPCZrRqq9LLx85NP/1S/9T/1uuu7oX3ns3NTaK4Q7cbcfHC81x47lnObPfpRAYCQ+rBTVKeuXgZtCYxMSpIkKCL9ZbtjQ2+6PWvZ//ykPdc/ACbW1tsnz3F+dc8iCdgmuR84qOP4lKPWMXefkE4fW65//xdvObue9g5cRIPXNnf5/KzF0ifeYZAG7bGWzhx7Gz16cZ9nn3qKfauXuXC8xcA0EHAwdY2WydOcf7+Bzhz51nSNGHr5Gk2+x1ObG3w8Mc/wfDggCzL+PBH3sdHPvY+Ah2xs32Sz3vdm3j0sU/x/IWnSSdjBE9gFEoVgZDyPEVUkaJlJeEs+7ue5kVEFp8GilylNMpqrUtbXXfNBQTn3FqV9JgS0mP5rmvx8oULHT/zB36UNwQeCG93c15SuMv0+eCXv5O/cfGt/MJvveV2N+clifZ916LF7cHfP/cu/urZ3+Ar/utfgKuvzEXIm81T+gPAT4pICDwGfCeFc+fPish3AU8C33LUyq5Hhaww+y2Hl191/LKSByyQuuX9h7fnerBY77VJo6wMLrSi4htqlxT2l+v3LWCR6FY+rOuMd/2aeprlZMHHtHmu+f0sKrTWzvYV3x13nDrBYDDg4GBAkkzAKXAGVZIyHcdsbG7z4IOv5dKVA/b2x2xvnaDf7+KMJs80iNDZ3EabmNHuECcBeQ6RjjlIBuxfPkBpzebmBpHZRuUWZS2nz5xEBQFbd5xmkmdMbU6aWYaDMd1hB5smaOU5GCVMMo/XAZ1uh7jTYXOzR7cbEQSaPM/J85xO3MVax97+gCTNER1y9tRZBge7DAf7oBKGg32eefpR0mxKp9tFCzib4/MUpFLZV9+X+r1dVj/rzqeFP3LzHiyP35t9Ho4rMeUWv+tatDgMG5LRVW1O0htBX8V0dXq7m/FSR/u+a/Gi4xef+Xz28w7/6+n30VevrCjiUARt21YWVnsCvSJwU6TUe/9h4ItX7HrHjdR3rUnp+n1zJa2pdq4hsIfUW03EqyyK1ztRXm+6u2ia2yR1q8jy6vrrvw4neHPCLjPC2bDuXTC5nJHGQ5S0hiq70sRTVrbMV+2o1VX/LVWUnoWjZ/7AS4GOCmKapilKKYwxZFmGc4677jjN5UCRJmPSdEKeOqyPEFUoh70gpnfyDF/81rfx4Q9+jOHoMe644yxhFJIJWG3QRrF56iziHHvPXwUd48XQj/vsJfs898zzbJ/cobe1yentTbLhiHQw4uSZE8QbfcKtLTLvSXLLh3/vIwwGI7qDDnvpGJsnkGfkORB06G+fYmOzz4kTmwRxjNJCkqSkSUo37nIw2OfKYJ/RNCUOI+6+536e+ZwwPhiRJRP2kzGj4UW2Tt5Bt7dFYDRZMmUyyMpb6UtVuwwOdYj/8zL87HmoVPjKd7Q+Jo5kWb7m2TiK6fDtxq1+17VosRLCzSdqa4GqwoUfv1fJSwLt+67F7cDzD5/hp548yfd97bvpH+E9KGEAk/ViSouXHm5WKb2FcCVxKX6tzUyxGIRFBKh8Rzz4yq9xvXngtU1Z52rpSvVoBeoBXKrfy5PriiR6EFWas66r27P8f1RXa395TL1mqW9ZceZa3/qSA/pym66ipC6c8jA1d9V35Zv1Ng8ur0oKxbLermqbKxuoGoeVfrWUcZGVIksSrLUExsxUQKM1TkCLxbqccWqJTQB4kmnGyTNnOX3uHL/vK78K63J+6qf/b05u3cl9d72KO87dgwkCnIOrl59jMjrgkYc/RhxH9Df7dDZiRGn2ro4ZJQkOx+lTJ9ne2iSONK7fw5126DAmyx2jvQM6vT7dqMvd99/PZDJmuLeH9yne5xglgCHQEVG3R9zfIIw3Ea2xNufq1Ut467j7vnt55NOf4uLFi+xsbWC04rOPfIJkPMEYIY438N6TZRnj0YQky+h1+ngxZEQYsSjxOGeLHvQeue48wL6xwFHfNlOwmavc8zK1BSJfNyUv7+rCGDmOZLRFixcTb3zzZ/n+8/+VVwWvTNOtW4Xv2nkfb/kjn+XPv/9PYJ9rFecWLV5u+LatD3HxNzb4tZ9+K+f+7rtvd3Na3CIcI1K6SESXfSNXfYe6ilc7tGZuWCu5zHYbAmZdZZ2f6zACe5hP3OGqT3F9i+rRalPhxcbOTTJX1ryCDK8UWOttp04hClJf99us2rhY/xJpXRSHG92/cL4aMW0uakvjUKlk0WpRoeaTWPm11tsoUlyv9eBQiCoIU9zrs33iFEoHTJOUq1d32e6fIe5EJGmK80IUdUmznOFoRAb0+z2iTkyQW1CW8XRK7jxhp0u316XT62A0ECtEGZQTHB7nHcoYwihi68QO6kAY7F4CLCIe0RptFMoYoigiCMNioaK8jjxLsbmlE0UYY4jjCK0EBYhWZKq4WwXB9GhtCl/NLCMPc7wHpTQiHrxt9N+q+7Z4X9eiuHGrx/bCoojUVkIWNHoWY0q/FNTSFi1eaDzQv8w7OpYbDWp0Nthn+hVfSfczl8gfe+KWtu2lhLtMn7tMQhxnjG53Y1q0aHHLcafp8/fv/CAPnP/S292UW4bHsyEPZ6fwuTqS9dnLEceIlNaVuiYBrauPR8WMvtWIXqG3Ff8Wyk1FZOYHHUb21p7Le5rKbe2qGqS1eZ7FOm5lIKJrTernfVJ+/JxQioCIuoaZ5zpF1s+IyzIrXd9O732ZU/PwBQBrLUmSEAQBoVk9fEUrUBqUIQdEG/o725w6fy933X0/v/Grv06e59x796vZ3N4klwnvefcn2djY5I1v/EKefvIZnnv2Gc6dOY31Ad2+J3VjrE94/vJlgjDm7le/hv6pE4RxgPc5nd4Gnd4mykPuHCZP6XZ7xHGHu7f7XLmgee7xR9Di0RqiKKATx2xu9tk8sUUYR0yzlEhCOt0uI1EkyZhnnvwc/V6HL/+yt/K+9/wOWgu/78u/nM986tN89tHPMh6P0VrR63fJrcc6x8H+AUYb+v0OeTLB5g6FxiN4Dg/pdj3jsB7o6jDf7fr9m5U/0hlatGhxPfjTG8/zTT/2j3nTz/xFHvhfnrjdzWnRokWLFkfEX3v663nf+1+NeoVG3oVjREorglhMZitCs94Et8Ja4sSCGucL48/53sXSh7VttS/ctRSd5v5C1VrvZ1onaPPj63UtBjny3hdmsFJFoK0UqTVKVq2u2V9fc2NaF6RogWgstmUlfJmYZNH3cEF1XXX9UFdsq3WK+bmDIECXBHZVZF6jA6zzHIzGnDyxTdzvc+bO80ynGZ/+1GfoxF3iKOLkydOMJwOu7l0hSaYI8PijjzAaDMDDwWCI9QJi0OEQVID30Ol2OXX2DGI8ufcYE+KUJgOSyQQP6Dgit5bReMR4f5f93atFihcBo4Q4Cog7EZ1+l06/TxhH5C5HKw2lBboANs/Zu3qV/cvPc2JnB/B86lOfKkx7776bS5cukOUZSTIt7qIo4rCI2JlMJ4j3iGiszcp6DzfdPdyf2dcCJgl1/X31M7re1Ns5t3R8tfjUokWLG4MWRV9ifJsNpUWLFi9BSKb4vse/ia859Ul+YOfJ292cFxXOyys2FUyFYxFSwVOR0tUKXN2E9DA0yy0cMyN6avYpLl9R0bL59qMpRddnYjg/x/yc64hZnZzKwucQs90FIn9Y1OAlpZQyxyZz5fimTSjXHL5Mtuvpb1YctLAQYIxBab2mHwRjAqz1jCZTVBAS9zY4eeoMk2nCo48+Tq/T49TJ02xtbjNNEi5cvECepYyHQ556/LOMh0PEw2g0YW/vgOcvXuX55y9y6dJFvLdEccT2yROgFZmziDE4UaTOczCeMJxMUcaQ2pzReMilC8+zf/UyCodWHqOFKAqIOyFxr0Pc7RB3unS6XUwYzPwzBXDWsb97laeeeJztrU02Njb4zGc+Q5Zl3HnnHXS7HYxRJMkUm+fgPXEYopWQJtNS+dfMh9XhSvRRTMKLquY+pevKzWJTLZiAS7mQctgCRYsWLVq0aNHilQVJhU984D5+7uk33+6mtLgNODZKaYH65PRohGit2aCssJFtEEG/sL1R65HOfVRU5q5zkln5hK4rezhm11x+v3ZrpTTJXUVSafiBXksFW6x3qUytLu893vm5medM0fVFbstr1l9r5Fp/22Uy65wQRDGb2zt0N7fwSnj4Q+/n9KnTvP51r6bT7TIYDvjMow/z2jd8Pm/4gi/iN371V0kmY+KOwbtCVT995zlAkWWOg/0r5HlOcHUPl6aE2hBoCr9QpSDzMHUU9sIwHYwYDweMh0OuPvcMPk/pxoZev0fcjTl5agcTR5goYDQeM55MiXoxzuZkSUqaJNg0L5Rs7xHneOqJJ9FGc/b0aXavXub5554iCAvfszCM8d7ibMJ0WpDaOOxgrSX3OcYYwON8tQx3fWO8obx7v0Q460GP6vdj3WLDgotrixYtWrRo0aJFi1cwjhkpnSt9S3tKjunrRaEwSazCulJ8X5+WZdX5ZBYQacGdtaxj9q1mVluvwS+ds2ivb0zYq7YeTX1cJs/LeTqlNJGd+21KLXzMsinsAvVexc1XENFZ30qtzMxfdEH1pAgyBOBrJNVXJGaN3+1aVIcVBy3sK69d5k0qyKTHK0W/v8Fd586jBJLJlGw4IOtvgHUk6ZQkTRhNJkynKWmaY5TBag0z31aDVlV/evAOvMXblCwZMxns4aKQIAzJ4xyXCxYHWVqYVCvLdDxiOh7hbIZWQq/fo7fRI+7EBEER6EhrhXPFOLLW4nKHs768do+WaoQ6ptMxxmi6vT55njOeTulrhQkC+nGX6XRMnqZFPwgU0ZqrZ0ohAlo0ztv14/CQ4bnsHy3zxZXF+yNSey79bOw3R0u9rmJby1RbtGjRokWLFi1eeTgWpLSY01b+ZE1/NO8rNXCWObQsVf0qzU4rEackidVkuO4l6bynSqsyP3k5q14wWV3jXVlrY/VpmuEu+pxWwXlm7RcWyNTqY2fbqNrscW7BZLVOFL2am3yuVDld6V+4QFG9q5xvK3aBqll1y6y/bU0dq46v95HU6ij3VNfjPCjw4pAVFuP161YiDc/fipS68lSqqAqLw1GkjlFS3H/nXXHO0HDffffy+je8mV/79V/l8qUL9ANh/8pV7CSne6KDMpqwu8Fjjz3Bk49/jo2oS2xCppMDwriDMiHJeIyIQomi2wkAjZIA7aaMrz5P3t0gjDsEQUyaTUkyS55PEOWJo5DpZEyaTAgiQ6/X5Y5z5+iUhDTLBoiyBApMJwbRDEcTnPW4HDQKozRhICjlsT6D3OKdYirFaAqjDnlprnvPvffz/DPPsnd1D6UE7y25TVBiSl9mh1IaYwxpNjmU+9XjvnnKfm1gvghUV/1FzX2m1WzRxM3upfeuNNWnYUpcLCYs3vEWLVq0aNGiRYsWrxQcC1Jaoemjdm01ba5EskKF80cUXVaZF8qa71U7q12+IMN15bRG/KrALb4K+rOglHoK89Zlk8fqvHXyS6PMvGmeIilopemtMdGlaWIp9Z1L3VGrZc1tkIVvDa58aATWpoK9zi8UqmtrUhS/4r7OFysEE4bc++D9PPvcFT76kY+SpgndTsyp7Q1ObJ1gZ+sEiZtiwoDt03cwHU1IpgkBBpcLeemvigij0ahYOFAK5zIA4ggyk5GlKZkbkKQp6IKwejTpdAze4dMEcITasLW1QRyHKCVordBao0wXpTVaG6x1eIEwDrCpJcsd48mE8eCAq1evMplOEKXAOrwHay1Ga7QJsDYlTzMuPPc8gQk4feYUly9fxLq8NJEtFjWKPrdkmcMvBBRq3K8lc/DlBQ7vm8+ZlAs79SWb2ehd8Dud/faLixNSGbazdtC1aNGiRYsWLVq0eFni2JDS+uTVr7Kj9czMbGGBzHhfmwivmFLXie7ifHdBIZ1vWiZWzZQWfjb7rle53nR4TqYavnkLvnj1669Zyc4VVl9ry+xnXRFex8RXK1CrSaFvXtQKwoks7TpagKRDTHdXRuSt/btUvtEQQbQhCCNOnznDM89c4vHHHsNrSxxH7Oxsc+rECU5un+TqwS4mDrnj7Gn2dw8YHgxxqcXiMMYgughclCQp3ju0CLnNATAqIs8ysjQjTzNUmqJMiDERWofYZIr3DrGaMAoIo5CNjQ3C0KC0lMRUIyZGlEK0xlmH87bwD7WeDEjThMlkwmg4JMvSeX/4wsw30AYdGDIszlp2r17l7Jkz9Hp9Ll58Hmcd2pSm6czHo3OWZjLZw+/Xql3zRZPmn2qELd7FpQWIcnwfNkzaPKUtWrRo0aJFixavHBxLUro4ra3Md1cd45wrTD5Ln9C6DlmVWTho/l3mpoOqND30vlLnlgnwvC7XaGaTUB8+mV5Hcpv7fWlyuZrDNfKiqqMrS+tUybmiNttUP1t5LLPGzCLmzuqtt3353s2rWa+QLv5WpSkxvlT5FiXTWvOUNgRBwJmzdxKEIR/54Ad4/PFnyJIpm9s9trY3eOD+e9Ciweec2DmBKGFw9QrdMGbzzCmuXtolU6B1nxyN88Lp06dxNidPM0ajfbI8w+ZTxoOc6WhE5j06MDiXIaWZbDeOiMKQzY0+3V6HTrdDp98hCAOiMEQbDUpQYZE31JVKrDjH6GCvsKb2BXENwojuxibjoSVLRzMrc+89STJFZSnnz99Fnuc8//xzXLlykd1dPfOJLQy5CxPaauHDBFX050LJX1Qyj5LmqLivZefXFmYEEFfWp9Rs7FSBrqrztWjRokWLFi1atGhRx7EgpSvo5pKKIshKYlrtnQfW8TUC0zxCjmIaWDugHlxoXeTaW4FVRLUipPUgQVIrszoVxwoluNHewxs8D27kF4I5FVvr5aSUcQvRrPAfrBS0Br+9pqnuQhuaunNte+2bLIp9AqKZphlpbhkOh9gsK8jh5gabG32EIj+oUZqw2wMlWJcTGoMxhm43xtoA5yMyJ+Re8HmGyy15miJYsjxFK4NSAVoFkGeIkiLViziUUkShJo6LdC9RJySIDNroIoWN1ohWiBK8dxXTR3AIDiW+9B72RFGIzWOCKEJNmkkHq/50zpJME6yzeOfIs4wiyVX1/Mw7apYuyKvD78MKQX2xfHPo+fJ8C17Ya8jn4gLD0YOStWjRokWLFi1azHHyoSvsfvtbOfXLj2IvXbrdzWlxkzgWpHQRc/Pdht1ooYauCCTUOFZKq9iabjoP1sPMlHH+2zd936RWvmZa2ySmVZTZJlGr/l7v5Ho1afM1YjoPAlXP63mUZDBHRVP9bGrOZYlVLWfm17raOnhWd0Wp631b7VuFyr/xkBbPy4rgleLZC5dI05R0OkJr4cTONnffdZ5eL2I8GRFtbLK50aW/fQJRijxLsNbhnOfEyW20LgIBTTNPah3ZdIK3FpeljDdisqyM1GsiwqDDcDrCe08vNARBSBiEdDe7RJ2Yze0eJgowgUGHQeGnqkCVEXfzdIIIKFVEwxUcUWjIU0uSOvobfcIwYG/vCtNRsMqzGTxcvHChtCTIocyxWy1QaK1rKrYru9OVyuX1ragcnkcWkFW+vs0NyybqrZluixYtWrRo0eLG8L4v/Dl2v2DMtzzx/ajfaknpSx3HhpSuM99t+F+qZZPPeo7ERvlGQRqEqZmmpaBJSqm5eWG5rV5nU/FrVr10uiNKqHXitWrCXv5aOtGNmu+uQ53cF76qi9FWb7xeqPqv2riohi4etOTyuKZuj3iP9YISRRhGTJMcrRRxHDMYTBmNBjzz9FP0uhGnd/oMAZ/nRN1tojimE0dUhqcmCIv2isLknsx68jAgSxKmI0e/38c5i7WeNMmZTBJ63Q7GaEITEkURcdyh0+9hohBREISGqNuh2+vPTFiDsEg1M/VpQXhthncOwWPCALyQZzmD/QGj4YiD4YA0S1Fa4/MqxctMnMZ7j9KKKOqSZjl5XuQh1VoTRTFZPsW5vHEvnGsq4UdBU9GcbW3sr3LSKqWwtlRsV9RRjN9WGW3R4lbjF0dd/t//9Dt44PfGt7sptxX/brjJP3jsqxlc7K+I996iRYuXE9StMltscdtxPEhpjXc2YqEseoiW+RdXm9LKWmLql3kdVZ7P8keD4Bbnm+cAlfK31NhtkwrWf60jiav8R2eNqW1r1j/rk3LDUvCkquYFlXXVeZdMomXxd/OKVkHqFR36Ipj3QxmTaaE1y8c3gigtNaDaWA2W+VYpiW5xDykInPckScJo4PE25sRmhyzPSJKEPM8JnUMbNTOrDYMQEVWYzypQ1qG9Q7zDpgEiGigIHX7CdJLQjWOCMEChiKOITiciiiNUYFBaoQNDUAY7UlIsehhjUAq0Vljv8HlBSAXQSuEUKCVkaUoynZClaeE3rRS27ILFbhIRgiAgtw4RW46ZQinNc1nov/pCwcL9q92kxYi59fszJ8T1qn1pwi2zBnpW1zO3hKj+tgS1RYtbgU9Oz3PunR/GjV/ZpPSjk7t57pNnWkLaokWLFi8hHA9SCmUiSo9b5HSH8J4q5coqM14A7xd94XzpV8rsuPq+CtbZWpmFL/W5dD3CyyKL8oc0vF6supY1hLGoWs+7ocnqahvmwaA09aBPVcVqVq46tuG32qhWzfupMun1zNPflAod4vF1lRWhCAJVJ+jl2Rc5u6quyTfu3+yKZN7FqrTJdrVOcr5ofxiGeGc52L1c3F9r2RuMGY0nZD7lzOmzbG326cYxp0+e4dSJM0wmB+yNd1Eeehs9Or0OLo+KFC2BQXKPyj0umRAqTf/kSfA5zuUkkxFdE7PT14SdLZQJEK2Ju1063R5OBNGKII6Jww6BikjTaem32iXPM7LMEgYGrxVWG5Qq8s86b8lIyG1KYKATabZjwzg3jFONF0XldVqRcHTRR9Msx+EQBYoiaNdkMik7XJf3rLh5smKmVj1LSlRziC+M66Y1Q2XeTpGyRpUhwLxr+nivsV4Q8WVgp1IB9sXdP6qlQYsWLVq0aNGiRYuXB44PKS19KH2lurDaP/PoPptzua2eU7EiVLN6Fkx1K7/KhrInMlNJG6a7tcBAM4JKNflfnFgvt9nPL3UlPOCdR5dhV+dq7VFqrvRdwEvZbr98VCG1LW9fUE2l9qOhfJaqV51IyAr7W6kR6Kq+QuVsmg7XlVipEZtV1ysiM1NR52zxWwRjDFobjNG4gvXQ6XQAmE7HCA4tHmdz0ukQ76aEUQetixylzgrOgXIWJRpV3AgEhxGLCSAODDou0sd4rQlCQxBqpMxzGsQhQagxQeFDqrQCb1FSkMJABzjr8C5D62B+7Upw3pOmKVmSFNFsnSXP83nwovq/ZRc552Ysfn6viyjOSirS2VSvi64terMyL646eN2wrPxVG+bY5fnmvtzFdl9bRFhUTKvo0nPz/JaQtmjR4uYwdFPeufd5/PbFB293U1q0aNGixXXi2JDS2Zy1xoDmUUbnimj9b/P4FUSoTnZEwM3VxBkJXSB5qvQrnNHYFZFxl9tSVwpnBRaOr0jt0Uh1lZoGX5Moy0l/PVDTKp/UFbUxS2PTOIfDi2oEH1pFuv2ijMtcHK5Mi4te8PMfq48ovpUkj3rfXaP9y369RXldmupW25QW4rhDHMeEYVgEPkrTwic0z7h69QKnT+ygtSJ1luloyGg/ZaO/iVYGQYEUnzDuoBCQ6ewKAkkxWhOGAcQGtCEXRRgpTKiIu515cCMToIyiE4UAZFmKFhAthEFILoWPqlYGUbrIYzotzHUnozHj4RCfFSlp0jRFqfpawZycFt1ZktK6Qi++yLsqQpZls3tc/zvrt5KUFr6gi72/6LNR3WdfkOxCyF45rhdTzlR+26oipW69pUOLFi1aXA8u2Jx//K6vRk1aw90WLV4pcN6vmuK2eAni2JDSyi+wprXM0FBxrlmPLBG/ua/i6hA7zRydUllEFvsak/918W6lSU4XiJ1zbtauimA32rXYhtl1MFOQjgqhMMF0ft7WunJ21DoWNwjLfadq5H1BOl04fKH3pDQxnbWvSfbrUZZXRen13pe5OIXpdDojrNUnCIp+Hg6HdENB4Xn66afZ3uyzvdFlOhogeLx3bPQ7dDqbuCwH71HegbjC3thDGERsbG1g8xxvHURRkUPUGGwAaJCoQ9jtEvV6xHGv8GkVQYcBOgjwrmhXJzBUOXedy/G4Ip2nFEQtnU5x1hIEASdPn2Kz32MQanJyRpMhztnZwkFDva7uh9JFVOE8nd0Ua3OgOe5WYdW4nN0D50DrJnGUglEWQZNcaR2w/JxWAcTq52hGsVaNc1XfW6LaokWL68H3PP1WfufpVyFJS0hbtHil4M3v/xNEP7XDzicfYXlJvcVLDceGlBbMp1IEj0aeGkdfYwI7C2x05GA+8+/NAECrlNO56WEziEutnByVEjYORInMTGSXUaWNWZcLtJ7iZWX1K+iu1Ewy5+2XWm21kksEpti+jrrXWlIS3VXEtPp9FPW7Ut7qx1vrSpNeh3cF+bTWgndoBT7PS2IrGKOJ44jUe3Ae7aXgVgq89gRGiEJFLhqvBayglcIYhRhACzrURFFAFIdEkUGUwiFFflKjsHlBvnSg8c4VUXxdjpSmvJ7iGmxuCzU2CFDdLpnWpOMBQRiWirA99NEoTHWrPKQFeXWNiETN+7q6juZYWhvNerbI4VZG811cFFoan36x/PLGNvhRixavXCQ+49Es56x2nNK9pf3WOz6TTcnKxbD3PHsfkyc3rmMJt0WLFi917D+2w4M/9Z6WkL5McIxI6eG4HtWkrrIsqqDNWf08t+JR1dglk2AE7+eKzw1QzyOcE/DNvKS+UkKFBilz3uO8K/et7rNmqpaFdDBHas+acnU238A8wNSM3h6BpNf9fhcD5lRmodV9q/ZlWcbzz19kPB7T7XY5efIkp05u84bXvZZ0PCAZ7bOzsVWYtQLe5wwGAzY2+gRKE6EQ4xEt6LiDR0jTlDAIUWLIkwy8J7cWHYEKhCA2hJEhCAyiPEpBGAVYXyiVUXcbRPDO4sSCgBHBlQpqMk3Ic4vkjlAbos0uYxmiBKJuBxMGtftU9WPtXsjcxFYphTEG7x3OW7wr8pPOx/dq4rf+nspSHxd/62bprrHeU6SdcY2xtVDpijYst6tVSlu0eOXiXdOYP/tr38U3fOkH+Yd3vn9p/xU34X/47R+AQVBsyA9NNtaiRYsWLY45jg0prQslQqnw0CRQSqmVZrmCNKxGpfxnFelZJKvzGuZt8I3yC78bMuJcIZ2XWq/2VGpjgxvXSOWSMjR3JZ1fFNWx5TlrbEBqh1Wmyr68ICmPL66xXr5JSKtL8VQK6YxpNGIiyUzn9KWyWqpz5aq1r3XkzLR5lv9UzdVfEWTRv7dGburtqeqa9ZX3s2uuVFNrHYPhCGtzet0QowBrmYyHiM0JjaETB2ilmE4nBEZhjCYQj5YiGFCRa1PQLi/Mtz2Is4hSKKOKCLdKIabIyam1QivBiEcrULo0ZJ2RshyhOA5fBJp2zuNyS5bkRY+IInVF7lKfZYwH+0xHIw729kgmY+YOEzK7l9Xdlpla7nCuIuxFfxZWyMWiQEX91inZ88FTji5fDbum6XR1z2eLC16V97ep0s/G71IE3vliUKW4+tlYqZVqldIWLV6xsF4hqeK3n3mAv7hi/yiP8CODSlsq2qJFixYvBxwbUlpxrGoyPNu8zj+09l15muTJ+8InsP7/qoX5rdTYZvW9Ku5qwYSaauOyqrjKL3TlZLpSZGsmvnWi1VCGZsJRQdqatHaxTl+S3aZCvBykSGZmuPXrWeqTRt0yI7fzayzrUnMT0Vn7q5ZU97GmjhZxm4p0MVISG1EFaZr3fUVyqg5oKmjV9VURdxeVXk8RqOfgYEQUKTb6ERqPSxP2d6+wEUdsxBG9Tgg4JqOEIIzpBCEBHsHi8ASEGEDypFQKNTgFXmNCgzYKE2oshQ+n1gajwIhDawo/URxaKbQI3mWgdOkHW1xHbh15lpNME8IwwmjF2ObYPMdmOYPdy4wHQ3YvXWI8HuLJQWoezguqtEDpc2pr91GhcDN+6MuVG1+788v3nMJddOFZXB7T1bJEOW7rvs+ecnGiUEwrX9J1+YObCjgtWrS4AWTeMnXB7W7GLcf+Z3f4j5/94pX7Wu/RFi1euUh89kIYJ95yiC/aGsnL7/18q3F8SGkdpS9l8bUZ9GZl5N3GsWsmtlJNo5nVtXzaZcK77vetxMq2HOGcdcXMOYfWekWZa9VxxOsq5d262fIsGFMJXymlJZuR0uyzbsopomZq6qKSOrs/jXs4V2Irxa2KECsLJteFUmoZT6ZMJynTkaV37jw+ivG54K3D25z9/SsoJURRiDEapSBJpoh4QgNJPiEVIe5EKK1QJaHURrN9YgfrLGmeok2I6IBAe8Sl2CTD+gzRASaMwOvSz1PAWlxe9J/yQhRoAh0RhWEpeAvm1Oki0u50Sogh2ZwQmYiLF58hmQ4RX5jJLue0nav/lY/xfGdJMsvxvy5U1/VhURGdB0la91xVJr3zcvOnca3vaosWLY4E6x1v/Gc/wPl3TVCTD9/u5rRo0aLFC4qfHJzkn/+1b+I1n7xy7P1J7/2ZZ/iDH/9+ft+P/C4/cuZjt7s5xxo3tdAoIn9JRD4hIh8XkZ8SkVhE7heR94rIoyLyMyISXkd95bfVfm7LZoDVgYUK5KU0UbwGz7oVE+A6QV7brsVm3iJiWz/fujqvpz2r6lgi5VAjlk1fQWGRqBYK6/zDjFiu8/qpFMRZOZlvE1act1a/Lz+5taRZRpKkZFlWmMKWfVXkBPWAI8tSbJ6hFUWKFu9wNsfbHPEWofp4RDxaObT2GA1aSfkBoxXaKJSiUCR9jnflx1u8y3EuB5eDL/86C+QoVdRldGUG7VBKCrNhpQgCQxgGxHFEHIaEJijS0yxYEVxz0aHsKynV1ZqeubLwooI67+75WC++FMRyrpAuR0z2HPJc+PVj9KjP04uJW/2ua9FiFZ4cn+B3pq5QAK4DDs+pj+eo3/pQa27Q4qbRvu9aHHc8nZ6g/ysfw37ykdvdlGsif/xJ4l/6PR4dnT603N2dXeRsgjev3Hf4DZNSETkP/Hngi733bwA08CeBvwP8A+/9g8Au8F3XU+8sP2fzXNecgC8ae66eEPulifPSuVd8r34fdaJ8WDsXid266/Ir2rOuDZVJ61FxFDKzcEDpZ6kW2qzAF6FqlRi0NohWiFagChNfUYLWeqZqNgk1wOq+qEhuvb2NNigpTLRLM20vcDAacnn3Kpd397DOc/LkCUQ0WZaTTMe4PCuKexDvCbxF2RTJU8SmKJ8RKsdmN2Rns0tghNAIcajodwydSBgeXCZNBhjtCQMIA0EbjzZgjEIbQWlfEFSf4X1Kno+w2RjIwCfgEvA5zmYk0zGTyYjx6ID9q5cZ7l9lOhowGuwzHh5AntIJQ05ub1MIrsWaYNUP9T5R0rxH6+7l0qJCfZssPm/ze7AY8Gh+/PLYqz/H1T2f3Vvm7a7vr9TUY0hIX5B3XYsWi3j/Bx7iW3/te3ksuz5S2qLFrUL7vmvR4vbg/3vH+3nPV/wT2Mxvd1NuG27WJcMAHRExQBd4Dvgq4OfL/T8OfONRKqqTkcMmzav2VwTOV45wdZPSOplbmCRfC/VjV31uBM1owGsKHYEvzgnDGvXykP6sb19V7zpCs3wPVPnRs++F5ueZi2iCL8mpUmp2bZWaWgmeq66jYYW6RFgLVMq4pyBqJjD0en16/T69Xg9EyGzOeDJgMhkxnUxJkoTpZMLoYJdkPCRPxth0ikunZMmkyElaRAxCAK10NcgQcXiXYe0ELZ5ACVorlNYobdBaUAqczcA7RMoMM+JROJzLsXlWfFzhJ6p1kZrGaHB5ymiwT5aMydMJk9GA6WREmqQoUYWJdk0wbRA+afbNKrX70PvKXPVeq4qvGB8Vkaw/F4vPSOPeyfL+a/0+Brhl77oWLdZBHCuTwO+7CX/umbfwT/fuftHbdLvwULDLH3jLxwnvGt3uprwS0b7vWrR4kaFFEYumEbn1FYYbJqXe+2eAvwd8juKFtQ98ANjz3lc0/2ng/KrjReS7ReT9IvL+cZI2zFGrCfKqafRKVbE+eW3Gxlm5bZWCWmOsS+ZP68xlr3fivDqlRgFZ8Vl3jlWk7Vo4itq8qvza/bMyqlBES1/RiiBWIY4qYsqc8tQUszm5rorU/Qyb5sDMSde8cIOgiRKMMXT7PXq9Ht1uFwRymzOdjphMx0wnE5IkJZlOywi3B6STES6dYNMpeZpg8wxn88JXsgzg5L3HO4fC4X1Gnk1QWIyiMLvVCtEarRRKilQwviKl4ouATni8LUhpnmeFaS8epRVGKwJdBEUajw7Ikgl5OmUyHjCdjEmnU5QojNaNG19XFlfr7dfGYQp8fRzM1c7mys/8+OKzfrw26zo0MNgxwq1819lhO8FucW2MvWHs0tnngnX80ge/gJ95anXAn5cj7g/6/Mt73sXn3/ns7W7KKwo3875rvOtG7buuxY3BG0+gj7unaIsXAjcc6EhEdoBvAO4H9oCfA/7wUY/33r8TeCfAuZ3NNY6iVdnqnHOzwBlRgXngnAbzXLWpCqQz5+KCm9GlQuODa3F1EVlLVBfLldfaaIhIqW4VV1medVFZWg5aRC3a7bzc8vnrbavMOW85ZlUW53Hl8r4umGMZWKcq4WcHVF2vFDNyWfREGQBJKhJY1a9md6V+7mLhQiG+8CW23jMaT9k/GJJnIxQBndCgvSI0Aa+6+wyT4QG7ewecv3OLODAo7xkN9zi4MqJ/4hSdTp8g3sblnnQ0BS1YY7B5jnOAEja2+sUVOcfk4AAVZki35g/a6SMmJO71cZ7SAV8V0YlchssycA6PwnlHnrvyXivIPYGJ2NzeIZ9MyYOUEydOoHBk0wFZnuHEI34+Phtm2zK/H0XHe5yab/LlNs8hiw7VM1UaHXgEt7AQUynbs0OqcV5fjpBZE5ZPIVI+A8v7jiNu5bsuuuful8hVt7hdUKnim//79xZuACW8A5mu+n9Cixa3Fjfzvmu86+5u33Utrh+u6/g7X/UzfFH0DNC/3c1p8SLjZsx3vxp43Ht/yXufAb8AvB3YLk0+AO4CnrneiptqZG3HgsAos//mW+qf4timsrP4lhSkppSvD8RzWBuPvn+BnJbbjnLGuZnr/Ps689ajtGmdOnW99RRrB8t1qbq57Tx8zqz9s36okdc1Z6NRolJeS9NfJVUQH8U0zRhPk9n1OWsJAkMUhYRBQBSERFFEFAQEgUEbg1JFoKE8TcjzFBC8s6VSWiib2TQpgyA5XJ7jrS2IpbN4m+PzDGwGlbpaLnRU6qpzFmctLs/wNgdbBFHC+/JcxfkKJRYCY6h3mYhHiScwikCrWjcsqt+++al3+8JYWd3VNRV6Zhp+BNV8tkBUXwlar7zOG0VjYWeVCe8xwQv2rmvRYgke5EqIvxjNPlyOCtPelyHe+8lX8UMXP5/Mr1ZGHuxdIjg/ekUH/3iR0b7vWtw+iOdt8TM8EKwnpH/r8mv4N5/6smIu1uJlhZshpZ8DvkxEulLMNN8BPAz8N+CbyjLfDvyH66l0ne/j3AdRbrH6V6h0+FJ5Q7GOJt2qSfK16rnZa1vle7mu3DrfwcUyR8W1yG6zLl8j5q4kdKvIzKoKax+lQGt2hxMuHQzRQUTuYX84pNON6fc7jEdDet2Y+++7m82tTTqdDiYM2dza5NSpkyTDfSaDXXI7weZTvE0JjUacYzI4IDKKfhyRTafYNEOgyE2qPNolaJcRYDHi0VhcOsalE3w6xU3HuOkIl4zx6RSfJQSiMAhYR56lZEmCtxniLVp58ixjMp0wGo7IkgTlHf1Oh36ns5bE132r15l9VwGGrucZOqzcYRF0676m14Ob9dt+AfCCvOtatHjFw3te/T99gPd935vZddOVRf7W2Y/y3re9Ezbb4E8vEtr3XYtji8xb/vMPfyX3fMvH8Ulyu5vT4hbjhs13vffvFZGfBz4I5MCHKMw2fgn4aRH5kXLbv7zZRi6Zp17HcYeRJCgnwFSmiqsJUP38Va7FdQTuerCKNMwD1yyWhcJ8Vxrq0joc5nu7ytz3mm1fQXQXldpVdS+2t17OVwaiMwm4KYvPq1pBjGeHeLIs42CacuVgyJWDMRthQJY7vBO6nQ6dOCI5uEpsPN4pXO4xRrG1tUM2FHLvOHXqNDoIweeAw3vHZLBX5Fi1lmw8AJvgRGOiiEhHuGSCyzLCjsOJkCAESiNBCGGEVgYtGsTisdg8AevAeXIBaz1kGXmSk1uLsh5UmReVHIUFl+PyjDxLCI1GKSHQUlZztCehec9q437NeJipo86XP+b3bj5m5ybZdRxWb/XsVM/c4nHHFS/mu65Fi1XwoecdX/xx3rH98O1uyq2H98W75hDoI1owtbh5tO+7FrcL519/gXfc8WlOqMOzDYlbjv1y7OE9n/2x1/CqL3qIj37jP6Kv4pXFIgn4njf/d37r8kN8+kP3vMiNvP24YVIK4L3/YeCHFzY/BnzpddZUr5PCz3D+e05aiqL16fAsyM01zrBqYg7gZ/5wc2Jar29xgr2KwFXb1gV4uR7Mz7fa3HbR3PEo5zlquTqWiMrStropbvOYxXZXwXFWqqVSu941yw2LPoy10yPiyfOcwWjC/mjC/nhKKKogfAhhGBIEhlE6xWYKbw1WhMCE9Ht9RmXU3V6vjyjBeQdYvHckkykiRT7RPBnhXYYOYiQIMCJM0ikeRWgUznly71FRhPKlj6kBMQLe4nyOtSnkDpzDOl+QSuuwSYLNc6z1aGPQQYh4i8KVCrIFZ1Hi0SIERuFzV6Q8rfXzuofgsPtfvx/z8Vv5Xs+fsvq9K4hnsX3VuQ473+wcfu5TesxU0ZW4de+6Fi2uD9546OX88J2/yl2m9bFq8cKjfd+1eFGhwAeeP37Xh/iLO08AL88UuCf+9e9y4pNfwPgb7Fpv2UA0P3jyEe4NL/O/ffieo6twLxPcFCm9laiTvUq7rCaqzrmZ+a6fSZrVcavn4jcyyV2t/Rzx2DVktfrrvSujsa5XWI+kWK4432HXehiJXod1BP5G0CSqi0S3JC84CiKkqx1VS1nY0IAH8jxnmiTsDQaMUsvUQZJbvGiiuMtguE8ygTxLsLnB2pBAaby12MwhOsREG+Ql+QxDTTrcxaZjjLjCvNY5Ep+jTQBBSp4VKV1cGdTJJiO80ngxdDa2UC4jG1tUECImKP1RPaFAbpPieDfCWk9mLbEOkVCDV0yzjOHBCI2hG0aYrU16oWKnH6HCkMx6nJ5wMJoyHDdNV/w1BnB13yvFcjG37eLCikhRZ90U93qwaow2n/EWLVpcC3/krR/kz53+Te7U3dvdlBYtWrS45ejcM+Bn3vxj3GUAOre7OS1uI44FKZ2FRalIXPWb+UTWM1dWit8laurpEolZMM2tY7atpgbN1L8V5RdNBdaZ3i5uW7zK2VlWqKDzCfuqUy6SuiKQ07KZr58Vl1oUIVlxDfW+qwhKRSSqNlbf50l6aqsBtbY2rrUWLrke5GhepEZ8Gn/rQZ/mtKXeaqlHMvae3HmG05QLV/ZIM4sSjdIaUUXOVPFF5m9tDDhHOp0gLgSEJJnirEfEYH2GOI9YweY5WZYVq3eujJAb+NLMrAhyJL7IReoBRQAISnvydIoGJIzK+jyS57OxmKcpWTrFe4oAR1mOBBaUxjmFzy3KZQUJtJ40HeNshlbzUWm0Lvt7blVQtyxYvsnzezQP/tUcc1Iy0PkijyyMl+ZT4b2bP2YrAxs1F5bm51+4q0J5ngWaukaJbdHilQLXtezcecDv3/w0rw56a8v97HCLH33yK4kvvnT9q/TumG/4+Lfx7fe+h+/dXo6fE4jm1Xdf4PH4JPmzLTlv0eJlAVUQ0rece5LXhy0ZbXFMSCkUU9L6dNWX0UMrQgrgrFsZoGUxZYhIjYTNUmCoBXYzZ2ueav7tUTViCmUkKF+b7Ks1qt0hSun8nGVl1V/UfDo/Y2clkVsZaVEtkNC5GWXD75UirYrUSMNclayaIuArv84lZjsjo7MounVF2s/PPetGtRC3WApCWLe8XsbiuV19RWLWH80yHoUDm+O8Z+Lgwv6Aj33mMRyG2ATEUQdRmiS3xGLYCAx6A1w65uDqHqbTJY5TtDgiE2N0QJZNcOIInSJPE9I0xYqQWc848ZzqKJQyaO8wInRMQDoZY50jDCKMMuggYDo4QIcJ3ZNn0F4QJ2AznLUkuWc8HJBOx0QaXG6xSYIzEV5pktyjtCEyAZN0TDJNuXzpIqEIsdFkmSFDo5QGX/lo6mqVY436KLX+rOV8rWH2THmo2wTPa1OIVKq/LZ9VW1twqG6aozlwPa7mK9ZUTd3MdBupm+9KeS0v01CjLVocETt3HvDBL/6Za5b7wd/5Jl79nR8AnnzhG/UCwX76UTa/Fv7+3/56vvfbfnRpfyQBv/LaX+Knz+/wvz37J25DC1u0aHGr4ULHz735X/C6sF1oalHg2JDSyqQQqE2cF8w9y0mtc27J9LAOX5LRJn9bNgVVItiFoCvO+wbvdOURlTp7mDHrtaPqLh0xq7ERSMbPCy/WWVeL12i6RXtXNGXp/JUv7Gy/NP7Wz9+k6sV3mfmDLgciklpwotnf5SYtNWqm1NW4UyPPafVNabCOq7t7HByMyHOH0q7I4ekdyWTC1Ss5w42IQDr0QkW3v0kcbOGVQinBFRIxOjCEKkJsRpomgGCMRhdBfQm0YLBInmGiCCiCK4FDiS9SxbgcMrAI1ubYq5fROkLrEKUcznvSLEe8JVAwGR2gvGCUBq0QHaCjkMk0YXd3j2Sak2eWAI2RIi60LhdpdBSTWwciDMdTbEX8fEEXG+TPFyO4/rysC3xUdfDMX7RSY2vm59WzVT+mysNb94eu7uUimmWk8XtefrWPdosWLV7euP8Xx3zBxe/jh773J/mW/v7S/rd1nuK7v/o3+InPfCnTz23chha2aNHiVuD86y/wjec/wjlz2Ky6iT/+6Nfw2M89xPkPP0X+Aratxe3DzaSEuXUolcjZJHdlodWpSVZNXJdTURx90M/aw1yxdVKptqxiluur8bX0HMysFOunKVq30s+0+Xcd5gSgRgrq9r++diUrJ/myRFIqEt68mNr+GQltBi6q71sipCIL92Sh+tm+MvpweXE1g1HqhqLOQ2Y9e/sDRuNxjSwVRMzanDRJyPMMay2IEEYRvY1N4rhDEBQmt4ggSgiCAK0NeWYBQSuNCBgtdIxCO1ukbKHwr8yyDG9tSdSKPKN5nmHzlDyZMhkOSEYD0vGQJM1Is4w8TxHv0AI2TXB5WhBfpVBaEYQR3sN4PCGZTMmTDCMaLcVjqvBoBXFo6EQBcRyVvLFQrf1CXy5GuZ2b7zYXEhrlRfDi5+r9zEy4Xqdffew1SGSdxC6P+bkifrN+zC1avNThOo5+lB5aJvEZ75laZHBs1pZvGvLuj3Dun36AD4zuX7n/HtPnB08+wrntgxe5ZS1atLgV8Bpcz/KOOz7NXz7xGFvq6Ga7H/rsPZz9x+8mf/KpF7CFLywks/z3yZ18Lh8eWi5WGa5r8cEra3H+2PzfrCItlUq60jPuGuaxdbW12lWZmIqoxjEz4lMzO53tq52m0uhsZRJ7oxc4Y6Bqbg68YJna9Act2u0ciFRmukc4+4yY+tIUuDi38+vV5XUkYLH8IpkoiM2y8racYuR6iPz8Xs914Llaa51lkiTsDUbsHQz5yCc+xXCSFqlYRNDekSdTNk6e4qEHznPyxAa9UKN8Tu5gklq8SxGBKDA4cnLrOLm5STadcPnqFaJIo1TIaLiLWIuxFh0EiNZMJhPiTp/ehmc02C3MTL3Hi8aLQrQGpVEmw/QhCg2DaY4IdAJNluc4m9HrxrPFA2U0XhtGwwlZ5ojCLnGg8BaSSUaWT5gmUzpRhPKCS8a4NMFnCeJdabh7C4lc5cPNXBWd73PNhZUVRHT+jK0/xSKJbSqlLVq8cuFDz499zb/kjeEBsN6X9D+Pd/i/vvnree1Tj9CmkG/RosVLAcEdY/7LW/8Zp1TIyzXK7qH4yKf5V1/z+/krf+Ucj/3x/2ttsa/t7vLFX/sP+JMPfxvPPXzmRWzg7cXxIKUzVVCaG1gmNKto4cqJcVnaN2gNDWLr1xDCOv+rSF3dnvSavqNrUWehq/1B680siGtpiiyLxy+3pSLaUjLpyqdzUS27EdRNl+dBdm6uTljuu7kwV6p2s2svdwpYiswqmYNpkpFlFlAFQfOKOAzRShVqpneIGIwOMMagTcBoMERwGAlxovAopqMheTrFuozcerT3KGXmsmx5bucc1lnyPAc84j1pkhBEMUEYICrASxHh1llbROkthFry0uBEmQDRgncOlzucL+ot/C8VWgc4V5wv7IXoXGNyg/KFt7C1GUpBFAZoUVgcLC3j3MC9gJr5bu3eVAq0+KIvyrG7aL676n5eLxYV2BYtXknQd0y4/8wVPi/Y55Ren/7lW5/4Sn7n4w/x2s9+CjsYvIgtbNGiRYvrg5xNOHdqD4DXbF/knutMbfW5fMgf+8ifYfsD0QvQuhcXPs/Jn3wKPbzr0HKRBNxlAjpB9iK17HjgeJDSm5x7rpy8SuEzWJCpytR0TgDrPmuHTX7rAYOOarq77Ada+c0p5tROzVS2RXVx/tUjM8XqSKeuEVOZEby62fH15CydpeKZtXr9MetSf8zatEJBre+HUpn1gFSkp1S+6+1HcCJ4ZfAqIMs9uS3kVV+2d7O/gUI42Nsn2+niY0MYxYRxTBiGXLzwDN5mBNIh8AbnFbuDPWyekdsEUodWEJioOA8ZYhSiBOUA58iztIiI64XpZEwQhfR6HZAQ6zyTSYLNMjIpso3iPVNyoqiDCWMoAx3l0wRnHc7mOGcQ0WgTYq3Di6Lb3QSXg00Z7u+SpilZlmN0QL8bcXVvhBKPrYj8NQbKXN1u9n35Y7atSUjnhtOewjS+MkpoqqKLz5Ms/G4es0hAK2uGxXItWrxS8A2v+Sh/944PwdosdgUe+eev49U/8bttOLAWLVoce/y+Bx7lX9/z32/4+HdP7ubsd17BXv7MLWxVi+OI40FKS9yo4rYuKMqifyMUE91r5Weso1JT1XWa7q7PBTpXSuspW5o5HaFo4tyk2dcbMz9LI7ppbfOMnKwKXnRUNPppNe9fSTbXRSJeRU5XklUPooprzrIM5y3OWZLUMp5Mubx7laef3+Xq3pAkszhfGFZrrdFKSKcTUhOQ5SFJmjCdarTzhHGHuN/n5MlT2HQM+ZgsSfCZp6tDoihAeprJaECWpXTjPniwOkfrwozaJkmhlmYpLp8iAt3+FlmScPnCBbZOnQMUySRhkmZ4PaGz0cdoRaANWe6Y2hTT7QEKqxxh1EGJxtkioFCmFWEnxCJcHQ8xCKEIJuqgTIjKHUlmmWY5Ss3V5aPm/jxsJLjV0YkWfEebhPEwpXTx2Vq3EFTkT10u16LFyxV3vu4i33nvuxvb3tZ5DFgfifJbn/hKHvnnr+PUbz/zsg304dOU9/z1L+U1b3krH/3O/5NIgtvdpBYtWtwA3HbO/+vLfpW3dx4FbkzlfNXPfw/nfhv6+x+6tY1rcSxxrEjpIgrT2brhKLPAtEebsxbqy+F8rGmK2jjRrBGHE7prBfFZ2TJfuJc2Gldda3nOUt8tA8vUijQauNDomTpcV4nrp1ggjEfkqvViq+pd7MdFks0sRNHcpLryGm36+xb9aK3FOkuSpqRJQpqljCcZw8mEi1d2uXjpMnsHY7w3qCoQkAhKhDTNyDPBWoOzHmsdaVbk/hSliKKQ3KdkqcNh8ThUEKK1QgeaRGvEKpRoUIUyq3RxJ0RbRGlEFM55lCrOm2YZSZbR3UxRKsA7S2ZzrECv30GJQkThveAcOC8U6VwMShu0MohkKKXQRrCiioBKeY4ojdOGIAjRxqOMJ3cTSIv8pVoLuEIhXxqC0nx+VliAr1RLqzs9Cy3VGN/zezk/Zk5MZ47czZMsf59bzN8C4+MWLY4/XN+CKfTNt555nO/aen6hxOGpET5y4RznfuJ3X7aEFADvif/j+ziXfjH2O/zK/0edjoc8upmjBqZ9ebRocYzgYgdx8Y7bOTXgu7eeIJDrJ6Sfy4e8e3I3534bej//3pfdYx7uCz873OJrOs+xo9uUOBWOBSn1+AaJacybfZUaVLC+UvzmlKvAKp86X9vXVOaWzQnn0+LFOXt9Tr8wvV9/PYdEGZ2l1SgrXJy7V0S0UEVl5hta7ayT06IaxZwQuFmDZ760lcmwP1wxbURjrT41M0ut5vsqnl6ptzN3XBFkZlBWpNsBwZX0U4vHS/ULEIdCQ9knzju8K1JlPnf1CtNpQjKZ8vwzF7hy+Sq7iSPzkIpHcof2ms1OB+ccaZ6j0HgLe4MRgRa2NjbwRHgCkjxhODzAKEc2uorPU7zz9OIO3dhgncN6jySOjc0djBbGw1HpZynoIEYbg4o2CExAGEUMdi+Qp1MGgwE2z8nznP1LzxJEMWGnh0+nYDNCv4lymhQh6nTphRF5mhV9bEK8EzLncConCCM6UYfPfPpRJpMp5+88g9YGpTXGxChRRZ/JVWw+ZaMXodOcbJhgrSr7fGF8i8NBQYwpU+GsUDabpBPwdkY43WzcKsCh8Hhny93FPRdVkGM/G6Dldj/XcGeW8L7Wytr4mY27NgJvi5cbBH7kK36Br+sWkSO7KgBaFfBG8GP3/ipPns/5uv/yF1BDfbub06JFixKve93T/OSDPw9AIIpA4huq54995M9w9juv0N//0MuOkALc8w8+yI//xNv5xC8/yd84/Ynb3Zxjg2NBShcxI3PV5HlmgnpjGWwO96OUufK6RkBcedSCD+W6cy6Wr38XWV33QusaJr6r6quT0LJkTbSaB0laGVBpoc31fKxNtbM0vZ0lca2bRM/V67mwXJHj5snmiwrVwY7cWaxzTKYZw+GYwWDCpd3dIpXKNGd/b8hwmjHKIQesCKHzaJnrtQXZV3glhEFAGAaEgcYrweKxuSWzjsx6TBChjEY7gydnMp0AoLQmCgxKK5QW8HlpFhwQGIMJQiy6IIkmwMQdRBfpYqZ2Qp5NCz9RSUjTFJFCSU0mY9A5qcoJoxgjitQXuUu9hzxLsc6TZR6NINqwudmnE0eERhWLMgLZtMihGgYhSoQgDBFJinWImflu0690frfmZHVuQF67gbUxUCes81Q7teeocXxNQXWzShr1rXtGGvXM+HBJZv3S6GnR4iWFrQd2Obc5T12ixPOm6OkbWhV/Lh/ylb/7fXTedX0BQl7K6Dx1wOt/7fv4ti/63aVJW1eFnNQZKxNyt2jR4kWBP5Xyefc819j2R8589JYof2lusJev3HQ9xxVuOsVfvsLUtQuTdRwLUiorCNMqM1Ml6gbMZNcRuWpb2QJRs0n9TK1slJNKPixUwpUK0/z34nnXpVO5lu3R4jH1uud5J5dsNqkTCxCUWhdoaJlcr8wHW5ZUSpVEZVVrD7sWoVDZ6u1wOG/JbEqa5uztj3nm2Ys889xFDg5GZLkjy6QIriOeBMF6wXshmLXb4WYEzyGi6XU7dDsRURjgFWR4yHOy3JE76HZ6hMoRkTLYv8JgNEAHAVEY0unEBSlVDnyGEk2oIuIgwEQRVgUgCi+KsNPDhSHGOdIkJ0ttEUU3TRns79Lrduh0O4yHA5wKSHXAxsYGRqoovg7nHOPxmDy3eAnRzuNQnDp1EuUhmxwUPA3PaDzCOfCdLqIgimNEjYoR6zzeuZnVQXEfi36vxrI0Fg1qpHBGaKvfzZyx17KVP2xh5rBndWnhpjyXd9c+Z4sWxw4Lr82/+Orf4Ns2Ly8UOnpOvgrWOx7OtnjwB/fIn/jojbfvJQb78Gd49Z+Bn/jnb+dvfH2rJLRocSxQe8/de+cV/tOr//MtP0XmbZGBoAUK/4rycToWpPRaaE6yKb83lbobrxvkqKut5cBYF2G22db1D9Q6Ar6aNC+fo+mrOW/a3LZ3UZWVte2qb18VMbdRP2CtLc10S5/Xw66zJKDW1yXhegTiQikcDEfs7Q342MceYzxJmKYZ3mnEF6aiBQkERBXn9I5AG0IRrC1IKUrwqrh0rRVaFwrjYDAEF3Pf+fN0opAoCnEuJc0sSTolt6BNSK/Xw2iFtZZpkqJwoANEGbwxWFUQ+7jXJUkzxuMJmoKk2zQlCEO2d7aJggDnHIEJcVaTTCAMFYExdPt9JqMB08mEjZ0dPIbMOqBLljvGqSW3lnwyLkxereXCM08BCqUCNrd2CKKIqNMls47AWk5bTTyaYv0uw8mEJEtqY7Eyp66ZvItDyvFR5fUVwNoiEnQlyy76bR9GLusBsa4V6OhaaJiRt8S0xUsEb/+yh/njpz7Y2Pa2+AKH5Rk9Kh76hf+Ze3/JET33yiGkLVq0OJ5461s+xTedfj8A95kr3GgAo3X4aDrlz/7vf4m7Pz54pfCwQ/F3H/h5fu/cffzIb309anxj1qIvJRwrUrouYm2R5mQ9sbpVkNq/qxt4+PG3on1LeVnXpFqpm+VWamjxa8E8lmagp+U+btotH4UYy8zuWBb2N+2RC3FZambKUmufJ88dWZ4WpHR/wNWrA5wrcnEaHZQHubnhqVRXVAU1UuTOzfw+/czg0xfmrUbjXaG8dbodQhOgtUa8xaOxXiHKYExhDgtlvlDxoEB0gBiDikIkMIjRaKOR3BZquXN4W0QGVkoIohBX+620RmmDiEIpRRhoJtMUaxO6/S6iDOKL69BaoZQvVE8RnMtxeUaWTlEqQAUaHWhMYNBGYaXohyiOySwEQYROE2iktJrZcDOzra35KtcDa9X9PhexZBXgmyNstZ/20RXSFi1echDwJ1KULsbyV+88zDf2hguFboyQZt7yL/fvYd8WJnBn3iuEv/J77QStRYsWLz5U8a4TVbyB/uCJj9fedbeGkH42G/LzB18IwEcO7uL0f3mS/Jlnb0ndL3V8QRhzh/4sP2Icxazv5Y2XBCmdk6Drx6q0MIcfUKR/qdpTb1s9Wmh9/41Osg/z9Vxdvk5IpVR5S9NjXyliFcmsEcXiqOto1+HtmfUpczPn6vfMHHjpqHlSHV+KcgcHIy5fvczjTzzJ/sGI3Gq0CjBKiHSI844sT2aekM5ZAIyAOFfS1fnleiU4gSRJMHqDUzubGBE6cYQOiii3ShlCoxAfYYMQZUeofMJ0cAXEY8KQeLNLFIdMkxzTiejubBLqAK0MToQgCthQffaef4psOkZLaR4dCHuXnsN5S9Tv093q0e3tkKZ5GaAoB5thk5zLzz2NCSPCzga5xHgxxHFMEEZEcZf9q1fIs4TNXoduf5Pu1g6ZLyj61GUkaU6aWYyJCEOI4w7Dyag2NmpmvADe4qVy/i27zVe+uB6jNB5P6mwtmJZvjPHG87BiWx3WFvfqMBV1Fdadr0WL4wQXOf5/v+9HeXVQPCyRGG7VhOFz+YR//+1fhTz8GABbk9+7JfW2aNGixfXChS/cu67C93/2TyB/dK/44RPcePeW1t/ipYPjQUqPwMlWU52579sylretzjTqG36ZBa1b9q/0VRSfBUVpcaI+++abx6/CUYKMHjYxr3xS50VqNHFW78wbtHSHlVnAqDLJySH1zwmz1LZVxzbMcEv5TNCzdkulkpYm0h5hMk1JkoQLz1/iYDBgf3+fg4OELBXCwGCUEKiiFuuEQJkiaYv3CBajNRtRCGmGtxZKU2JdfhQKhzBJcy4fjNjpRURe46wjswm5SzCdEMGTu5xIKYIwJDPBzDdVdIgJO3Q16EAjDpwA3uGdL/xBc4cJDIoIIwrvHM7lxJ0uzuV455iMh+RZYQZsXICZCjZL8c4SRBEiHpunRN0eKoiwUJode8IoQilFHMWYMMRExYqkc54ss2hRhEYzTRx4h9YU6qwo8jynkjO9Lw14KyXYe0SKu+58Rev97LvMxm7p11l+ZPaclfd6XfCiFf7T61BVMR/jL4wFRIsWNwOv4NWf/xRnOoPZto7OuNdYuurWhPL/96M+f/mXvxXxoKbCQ5/7LHY0uiV1t2jRosWNoP+qfb7s3BO39F1Xx64d8+Zf/wG23x9xZvTMLa//uMNnOb/002/jP3zR5/Oxt/8bAmkjiR8PUsqyT2N9++w7rmEqeM0gLLJAMJGZClpEmfWFUeOi6SHL0+OiHdVEv6YglTUv+dJVdTWCEvlG+6XJHlfiaCbB1bnL9DCyQDVntq9SnrRULaufsrqdzWtvtrToo9Jctgr/CshsSLlGaecKMjOaTDg4GPLpRx5jPBozHk3QOkIpTRgYQg2B8lBYyGKUQXyRT1TEExihH8dMbE5mLXiFQqFFA8V3j2JUktJuJFhvcNaS5zk2y+iEWyjxZDYnDgVjAnQQgsux4lEmxARdTGQAh7N5QdrEY3Nf5Bm1Dh0EBBoC0eRpRpY4ut0euc2YTEdMx0PGfkzc28K7iCxQBSn1DmO6eAFrM8LQEMYRU+tQSiN4wjgmiDoEJsZj8T5DlCpyrk5HaAkxxjCZTPDOonRh0iwI3hUpkpQu0r8IUponC9Y5tC7um6tHzp2N35J41sdzmQO1MgP2vrifS6NwRXCv9QHB5rlpq7rqwbheKBP9Fi2OCl+a5nrj+Zv3/3u+NFqMknhjkzTrHUOfNLb92wvv4KG/9HtFPizA3lDNLVq0aHELIMVi3B+97+P8yJmPcaPvulWov/8eyQNe9/eG2E984JbV/5KCs5z/O+8m/UNfTPY225JSjhEprbCKDF3zmJJgLUWQFRqT3FXxjApeeO1gLPOAQXUz2TXHrNhcJ6TNQEW+0cZqIr9ucn4Uk8ZlQs2sL2YRf+sJWK9TofKVj2JZh5ozWzz5jJ4mmSXNc569eJGDvQGXLl0hm6Y4axEHWEEIUKJRAuITxlNLnltObu8gGqaTSZEoXiCUELHCwWBMwbY01nqUBq3m15ZZS5ZbkjwnsZ7UQm49eW4L8pg7jBYQRZrn+Nyioy6dKGTzxBZBEKCVLk1bc7yFNMsKxbAkU0rAesgtTNMp3lq89eROQALijVMYE6C0Ic2yknCB1hq8BqsQpdGiGQ/2SaZT+ifuIHeQZI6w28eLYjiZ4m2GdxlaB2gUW/1tpklOkmSMJ2OS3GHiqMijqhRKaeq5excjNjvXXNwBSl/eQkVtLvpUBgIFGfW4FQrn4tg4fNuqQF2r9rdocdtwKuFfvO0nCMSicbwhuHWm5P9i/25+9s//YXQ2X7gz+wm4l2/6gxYtWrx0oO+Y8GNv+XFeG4y4FcHa6vjhS2/kPX/pSxDnkdyjP/upW1p/i5c2jg0pXRfg56ikbCnYiqyrozJS9HOlj1XBf9bAC/PJ/tH8NRcJ6aISeZi541FNIeeYt6++SaQwoV3ev9y/DSK/5r7My9brKNVn77HOMhiNGY2nXN3dZ7A/4OBgSJYkiPNsdntoJWhdkT8IA0Vuc3Jb5C11vurughwZFOLBOleEyabIm6rKQEKVcm4t5CUxtc7jKAio1gYCxzRJCIyiE4WI8zhr8V7wKJQOcL5QG5UqzV8rEoZALWKtSEEskZyiMIBGRNBBhDIGrTXae5TSaBPgRIEDpQJQGq8UNs9xXgrFsAxE5Ms2i9YF+XceEV2YRPviWq1zRRAlDUY0omTpnvjavarfv0UFc5YCZqF8pZoWXVvurwXWWqyjep5m2VIXzN2LxSJpENLrjdDbosULDaU9XxGn5cq1AsKbqu83Jpp/d/VLAPhvTzzEvb/1MXyWzva7dQe2aNGixYsAt5kTbRYK5oNnLvMVMdxKQmq94/9z5fP4tx/5Eh76zQ/NVqXbd1+LOo4NKT0KVhG0mYJJLYfm2uMWSNksokutPip/Sb9UxyyYqVtQeQ7hjHXVqWm6u3pSv2rfUdA4Zu38vq7uSnVgow3rAkOp2u968JrZcaiSSEGWZwyGYx597AkuX77KaDJFK0Ucx7gsx3tLGAWI9niVMzwYorWws3MSvzdkkmSMJmNQmiAMybMMsTmxN3gPmSvNrgWiKEQphVaKPE+x1pJbz2QiDENNarexogiiiFB30SI8+dlHiULN57/htWSjfdKJYzickOYeHU0AiyjY6PegJNmBKTKjJqWfl6cw+zVBgDFBcd48p3TgRHSAxZI7RxB3CIKAqNdHMod1njDaQFTh7zmaTMnTlOlkgjIR2gRkWQba0e/3i8UE8djcYlPL5GDMNElJ0oTeRp/IwzjNASn9SdeMi0NQmLMfOniqu71076HwVXW1fU2KWz/RvMCSZcNie1qi2uJlgj/7m9/Ja77nwwDc4x7Gu9ZAt0WLFscHX/WGT/HOu3+7tuXWBjM6cFN+6wfeykP//SOHu921eEXjWJBSQZYI5WEKHdQmw67IY0lN3Su+rJsQu9qPwhS3rh5VtHVlaho83i1vO+oDtkoh9d4XJp0sE9jFY49CWlf5ws5V0vm2Qh2ebVjYNz9n9Vdp3SCm9XLOefIsI81yHn/2AuPJhPFozP7eHsl0iniPDhVxqDCbPay1DCdjTBDQ3QgwuoPgUT5H4VCAzTK8OLwKCLUQGkNgi/ujtGDF4CjyaxZpXAqxMtAan2UY0YQmZP/qHpIlXNjZZKPboRfH3HHnHYTGFCTPgxdNt79JoDUKXZBK70kmCUGoieIueVqYHSOCVkKgNWmS4Jwr+kUZTGTKHKAK0Cgjha+nUQRBQNDdgMyTO0/uy3ujDEEcoD2kWYryHoMjyS1eNAbBa4VTgglCdGhQsUMDRgsHgwnWC4EEGKUwxjQCHRXi+OpnZ6W/p/jZWGumf6kfs2JszrXRYkyUD0otZW7lzb00SNeNudaMt8WLDoHXf+ETfOXJz8ziD1wv/srzX8h/+sW3Nrbd/aEcv7Bg1KJFixa3G24z54++6SP8ke0Po+XWEFHrHQ/+2v9E/OQ8ZYzkcP9nnyRvF+RaHIJjQUpn/o4s6nhS/7GEutnh3OS0Vmm9/pKEzubeNZ/KhiLjfeUeuebUc8W0+r6oCC3qrHUFSkoSXEy6j0Jml0nAajVrXq45mV/sF1b+nh0nyySh7gNY19NEKbzz5JllMkkZT6Y8+sQzjEZjppMx2juUeDpBgBIIjBAEEXnuOBgM6IWKTrdLZEBc4b8peLSi8NEUAE0YCloLqlJIVWFq6wFni2O8OAIdFoQ1FYwUxHF4MMClEy5fuYrLNlAezp09TRgYrE2wrlA9O90+RtXT3DiyNEUpRRBEpElKntsiR6pSmMAwHk/I87wIlGRUkQNVNB6F8wodGkygUEbQJkBHXZwGbz1ZMkFEYXSA0QaHkGQTlAVRQjZN8QjWRDijccYQhBoJFCp0aO8xeNKrA7yDThSglSp9SgXXMDOfL2Yc5vNZLbAUwYfmqy8zC+oFMts02W2aCvvZhnJczoZUu0La4njCa48PPH/hrv/COzqW61UKrHc8Y8f8wsNv4sH//d0vTCNbtGjR4hbBB554K+Hv3/memw6yU73/rIepV9z3M4rwV5rvwXZZrsW1cDxIKSCzlBSAL+LDeppKS6P8gplp5SM621/+9cAsPeMKf1BfmbS6mnluPXpt6QNX+TU2KKevm8PO0dhSFq/OU4VJUhX9WUkUPHg3C8Ik3s06piLr1V83l7IoSLcgmBqpXzDXbfZiqTJX112d3heRXMtrL0hJ8cLSkhU+l15I7JThaMJTn7vMxYtX2dsbklOY2IYibG/1iCJDmmY459k/GONdUe+JnZN0O5pebAj6EVmWc/H5K4hWbO30wAsiGqNDxqMJySQhB3I8aerKnJ1CpxMSBoZOZAhN0caxUYiGwWhAL4TMOR59/ElObm9xemebq1evsLXR51X33cMoTRmPh9x/4iQAe4NBUZfWOJswHY9JJyPCIEBpBWKwXpjmRaAnJY4sm5AmRTqZTrePCgJMFOOsI5lCL47AC8PBCC8RiCHqbhe+lUrwqhgNoY3xzpF7S9wrot1NJiNUGKJ9RDaaFPfLCz732NSxublFmuWMRgnWe5TRBEqwLiev+awVt/Vw32UaY2kORz1skoZKF63GjW8unUgV9Ko0IlC1cssLMfPx2fqZtrideOD1z/IPH/hZ7jeaG/Eh/UBq+avf8xd57acvtJOvFi1aHG8o+Etf9St8Xf8TBNK/6er+43iTf/pnvgszSMB74kcfbv1FW1w3rklKReRfAX8EuOi9f0O57QTwM8B9wBPAt3jvd6WY8f4j4OuAMfAd3vsPHrUxS6ante/rpqcz1bEstZiLdM6zlslZlXu0OaFuzrDLIvMJc82MtmrYKt+5xuS/IZ368izLbW2YL8+O87Pj52JTybIr9VXqahg0eKifq7Mr2yfgK5V5YV/Tt3RuLp3klmmaszvYYzCccPnyHvv7A8bjKXGvjwioQBEYRWAEaxVKlSSldAYt8nEWgYuyLCfLchCF0QqUJk0zoMi/GQSCdxqvBI1HrEUsOC8EWqGEIliRFpQSorBQLoNQE8eaQBeBj3Jrycq/ubWFX2gQEsUdpmmKVpow7mKMFO3NDS5PyZMEo1RhpivFdTjr0UqB1uR5EXFYpAjcpHRpAqwU4hVJkhb9rABlER2gdEH4rUAuRW5VrUJEaYzSBLpYWFBiEa0RVaT78d7jrCfLc9Isw/siwFJFOJUqIgoXKXiaY+tIRG9mSbCQeqkcIYsqaX2cVQtA1Uah+ZxUC05zV+7D23I7zHdfzPddi+OFrXDC68PODR/fk5zdB0P0+CTqyaduYctatLj1aN91r1y47ZydUwPe1n2EB4IbJ6S/Mo74P596BwCPXjjFAx9+FDcYXOOoFouIrkz5hk//P/iuu97Fn9zYvd3Nua04ilL6b4B/AvxEbdtfBX7De/+3ReSvlr9/EPha4KHy8xbgR8u/N42VPp7X4ctZD+Iz2w6zQKIynykvnrkkpPN0LQ1fvOu5iEPat7ClsX1l231tdk+NSNZ8ZcsN1NO/LCvMNd21tk/VvhearsN7R5LnXNkbcGVvwMOfeITJeAq2yK1plNCJCvNW5RSBcSgEEwhaB4SmyPPnnCfLCsU1yxR7e3tYa4mjLtoUUWRHg2Hpy6qIOoZePwCtcHhSm5NmispFK0tThsMxvhsShgG9/gZxJ6LXi+iFRQimJEkIQoM2ik6nQxzHeOfZ3tpBqy2eeuopup0uDz7wavJsis0SUpvhckuWJLjQFNZ8FbMCwjDC+YDJNCEIAsIwpNPtgdIk1hEERfTdC89ewFpLEOgiGq/WSL6FF0XmYeIEJ5rexiadbpder1eQW6UxJiDNMqZZBmhy50mmCePJhNFoBBKUaxSCKutOkineO7RWM8WyPo4Wx96RI1ofckxhqetnxgOLCxxHwarIwLcB/4Zj8L5r8dLD68MOH/qhf8brfudPc8+7bndrWrS4Jv4N7bvuFYkveugJfv6BX+dmo4r/5Q9/M3d/08cBuJ9nW2X0BuHf/3HUO+Cv/fNv5k9+/Ttvd3NuK65JSr33vy0i9y1s/gbgK8vvPw78JsWL6xuAn/DFrPI9IrItInd675+7qVYuBDFal/dw/eFN0tWYVKtand7jXZG+oyFszv/MLHjn+2sE9RqT6Ua6lQV/1nrb6mdcd211UtnwGcSjqIIbLRPaeh9WhLN+/lXnLM5RRJc9GEx5/uJVnn3+Es4qjO4U0Xh9huAQcgKt6MQRnU6EMRpjPZ04Zntrk4P9A5I0JQg0CkF5wZgQoz0bGxtkeUqWpURRUCqZGptZstSiAzMjhZ0oxEeKS5d2USL0+30CUwQ7Go+GiDg6sUGrkEAXyqwoYZokJHnOaJrw3IWLdGJDHGnuvPMcWml2d/dIkzE2SxCXYAT6m9torQqq73OyLCv8TbVCaUW32yfPcyaThLhjUVKxVwcinDp7mmSasL97tfCNVQqbTUFpRBl6UQ8xIToMyPOMvb09trZ3CJRhMknIbE5uc7x4vBeCIKDb7aBEUCokyy2D4WR2X7U2eG9Z1CKr+1r3F62PzYJNLgQ6qpVfHN+NeoSmTH8tQXYpcFfNSkDmZV5sHIv3XYsXFa5n+VNf8l7esfmJW1Lf0WIFtGhxe9G+61rcCB78ze+g93uFe9HpR1pHhRa3FjfqU3q29jJ6Hjhbfj8P1O2Wni63Lb24ROS7ge8G2OpGi7vr5aov193IOrlaHU134Xd9Pt2wPKwRz5o169yid7WadNi5Vx23qOIuHrWkmDYta2v7q7/N49cS3ManVEYXymZZRpKm7A/G7O4OuHxln1BijFZoiryeAmjxBFroxCFxFJQECTq9LpubG6RpAnis9WA93oLRBdkMwgCPxVohDAM8RaTdLHFkmUUZUxLpwmxXlMFmORIYwjBEKQvekSYJeR6UkXEpAgDpImhJmmekuUWlKd7aslzEuXPncNZx+eIVsmSMzVNC4+lGhrDTKXOZFiTMWkeSpogSjDH0en2sc2R5kWPViAbRhd+ld/Q2NtHGcLC3NwtE5L0t/JjLa9GBASWkec5kmtLf2EJrSPMc64q8rR6LiEKbQpXFg9IhKrOMpxmIFNdcRrJ2a6LcrSN7c7VzThhXmuuuqEsocsYuPTxrsDKStNRN2v2R6nmRcFPvu/q7Tu/svLAtbXHdkMjyv55+H30V31Q9mbd8Is2ZDNb//6xFi2OO9l33coYCFzs2guS6D913Ez6dGXZ+vcOJf9UGcmvxwuCmAx15773cwNKw9/6dwDsBzp3YXGE0W0h916rYObdk2rrmfCtVSe8KW0NVRp713mO9W0OCfe3fiqz6JfI4u4bDTI6vw4zyWmhc/6yOKt3NanI+V2yrBpTHqma7nHNYa/n0o5/j8tV9Hn/6Et6BOIWJPUqKPtCBRhvD1kaXTidkq99lPJkwTVLi/g4KzXgwZKu/Qb/T5dlnn8doTdSJQDxZlnLh4lOc2Nnh3J2nuby7R5JmTPIcCRShCjl3/g4Ez3Q6ZDgcMxlnbPa7WOcZjyaEkUcpMMqgnGCTHJvlZM4xTTKiMCSOYvYORnSiiLM7OwRhhyAKefqZ50kmYy5ffI5OHBGGAaobMbWO/Wnh26qVZqOziegEVEE6ldKgAoIIukqzt3cVbUJOnL4La3PSPMczQeuAe171GtJsTJ5nhIFmPJly9eoecZYTRDHx1imUDuj1NhhPMyaZJ+7EhKpQXwbDCd5ZjAmx3pNZS2hAB4bN7S38M88wGo2WlMfqPlb3vfpezze7KtDRKnJafa8/d5VvdnmChXG4jPriSvMZcXhc01f1mOFG3nf1d110z93Hhmm3uLX4QAJ//Vu/m9c98jnapActXuq46Xfd3e277rjBbeb8p6/6x9xlAK7Pf/5Pf/aPYb8z5tSFj7Zmui1eMNwoKb1QmW6IyJ3AxXL7M8DdtXJ3lduOhJl562yCSz0qyspJ6vWa9FbVeO8Rv5jOwlc7qYIJzdSjsj31IC1FHYddUHlMeTFSkoDq/MW+BT/R2SVXlLeuHqmyHLOcod7XSHmpvBW7Gp24lphW7W+Q1BoZmUwSRqMJV68O2d8f46wvzwN5rlDKoZQQGEMYGpTMXS/jKCYMPM47tBiiOEZE4UUwQYDRChMoAqdRKmRbbxPFMc57up0QE2h8kpK4lNxbRByBUYRBj/F4grU5nc4m1heBjLQuTIi9QBgaOp0IbQxKKaJQCIIQYvcW2AAArQpJREFUrQxxFBFHEcpoMmsZTxK0CDbLCANTqL8C3uZkqcPZnF43RoshmWbYLMNai9IBogKUNuWD5NnfTVAqw2YTXGnQXN2nNCsi5KIUmfN4EYIoIogiTBhibY5SBm0CLKpIP1OOR+9soYCiMEGA82PSLEcHhR9nnuWlmluSy9rAPkxzXPKP9uvMdytyWv4zU0SFyjG7GjtV4KXGeeo/hFoOyLolRK3dsvJxv114Qd53LW4/4nsGvOb0xZtOhwAw9QHBU1fIL126BS1r0eK2oH3XvUwR31u86x4MDJEERzrmBy+8iV/73GsBmHz4BPc+1iqkLV5Y3Cgp/UXg24G/Xf79D7Xtf05EfprCCX7/xnwOZB6qp64s+rkp7aL536LS2Ajm44sUFq6c97qSkM4m1r7QaGZwpZ280rMJdrUyJGqZCKvFhMPVxH0WklQo3AyPZp5b7J+rT3Vi6n2pTpXn9CXtKXlsGbVXH6oeL+4T5qpZpR4X/WnZ2z3gueeucOG5XaZJRjfskGZT0jxhmni0KgIZ9UxEpxuhfF6axTo2NzcJgoDLly8T6oit7ROMJxNsCnGvi8ZjFHhvUJ2IEyfuYjgcMBwO2Njo4j3occp+vo/NM5wdY+IuJ7Z3uHJ1F2stW6c2UUoXim46wOWFD2a3G3DixAaagsCHXYOgUWhObm0RRyE6CBhPJxwMErqdkMgodra3ULgiDU+WkiQ5iU2JgjsItWGwN8S7FFxK1IsxOiQIYrzOUUoxHo3w3rKz3YNgA4IeWgk2zzgY7hJ2OuggIE0TRBT9nR2ibh9lAgaDIdqEqCCexaoy4sjznCzPMTpAdEAURVgPo2lCEHVx1jMejbB5jngK9b+8s84XqWoWhyfer/YtZdF81+G9rY2XYlyr8quvUhd5v9IXtBHFF0DJ3PV0ZguvmGcp9jNf6GOEF/h91+J24X99w6/wP25cAY42SWvR4mWO9l33coTAD77+V/m2zctcz7vuP/3c27jrb7VEtMWLh6OkhPkpCsf3UyLyNPDDFC+snxWR7wKeBL6lLP7LFCHDH6UIG/6d19ugSukR0Q2StlxmZVuXyt3I5LZSNF/4afFhWpCs+T6/rrpprvN+bar3qnzdXHNVGZEiCE+eZ+R5zv5ozOX9ARf3DkiyDOcdxii6/W2C0DAdDhDxRJFhc6tLpxMxHe7jvScIArTWGGM4ffo01nkuX7pEFMdoVZDmbrfHzuYGTz/9NOk0YXBwAEC32ydJpjjv0Tpkc2u7CGQUgLOOg4MDOp0uJ09qdnevIkoRBAGGHCVCHHdQypBMc8bDAXjPZr9DJ+7QiTrs7u0RBIZut0tgFFEUc+rUCXCWZLiLeIsSz2a/Ty8wmCgkmUzZPRgSeI+gERXMfDhHoxF4h/c5Z+88T56nXN3bo9NXxCoAH2CMZmtri0makiQJYWjwSOGDqk0RybcLBDFKA2Wk4jTLyPKcLM/Y2N4qritNUVrT6XTY3d0lS3Mm42mReqYG59zSIk4V0Etq2+rPjVKqOM7Pie31RNA9FDWjh8JQwJeLLCuKHsEk/4XAi/2+a3F70L3vgO9/zW/x+ztPAjeeEuF/ee7N/PY/KYKQmqln+9KHb00DW7R4gdG+614Z6Nw34M+99jf5qu4T3My7rkWLFwNHib77p9bseseKsh74/pttVFnXkfxEj7J/fWCXBQVpFrSl9tsvHOHXmwYf3pbieKibzzbNd+dnmX+Zn2vZTHluNOkbJOIwLKq8C56ls33WWYajKYPxhIPJlNyWiphAYAxxHOOyMSKeTjciigPCUJMqmZFbpRRaa8IwZDKdMhyNinQoujCV01oTRhHe+0INTDOCMCQIDNPJGOuLfKdhGCIECCngSdMUYwxxLEwvH8yCBwWmyBMqqgiulKYZk2kC3tGNA6y1OGdJkhxrLWEYEgYxYRgVEZe9w/oi/6goEBMQRBHdfp/xOCHJcoIwmKn2SBFQaDqdoqTwZ+31iwjCw+E+1lq8szjnMCYgDAxJnuPyfBYAKnd2pnQHQYg3RY7Twm5XcHmhjnsRjAkQpcmnCUopgjAk3TsgSQqiWw9sNB/7c/Vz5f2vKZkvNAesokPPh/D6E94OQgq3733X4sXFmY0h37v9DNczSbtsR7xrehbr54t7v/jpL+BV//p3Z79bX6sWLxW077pXBs5uDm74XRe0KUdbvMi46UBHtwvXingLzYntPBjLtYmutYX5rii9snw9yMvRp87NoDGHqZZ1M+XDIvce4XJmdSyaOTdS00iTrFjxTPOcJ599nsu7Q64ORnREo0SR5zlXrlzGXcrY3gzp9TqcPLGBKFDKcuLEDkrUjPTFccxgMMBaS6fTYW9/nyzLUFozGAxIJmOGwyHeeaLQIErjrCJ3Gut8YUbrLSKebjcouJpzTJKENEsR5QijkM2tPr1Qg/dcuHiVZJoynSTEYREFeGt7mzRN2T3Y48TWFkFQ5BTd3t6k14n5xMc/SmCEc+fPsLOzQyeOuHLx/8/enwfbku15fdhnjZm5hzPcqYb3qvq9nmkahBsBDRZuWtiAJGwki7AZLNuYQViSQQiELCsc2A4RtkJGgIJBJgxqdxhoCGwBRkKgRmJQ6DXd0ND9mqab7vcaXtd4pzPtITPX5D9W5t6599nn3lv1qureqspvxalzdo4rc6/Mu77r+/t9f2/RBk+SmoTC2Irj26cE39CslxhjidHz7rvvMptOODqaomyJKSs+85rGuUBwDuccCSh0dglWxjCpSnyIpNSyWi5ZrRsms/nGcKtxHhBMywmmhEqA1IYQc46uNpbp1BBOYbVaEdxjICu3Q1Oj/ju9qQ/tb9eHbg8747NMEL0npN2o/EM4FFo8YsTzxL/z5i/nnX9xSgrbvvkNzZdHU6MRI0Z8otC/6145/8Fxom3ER4oXgpQKdhWbg0hpm4K2WbSbu/YkbBWatE31HJC/4fHEdsGghd2va8mge8R3f/W2AQNPl2cJTeyKs3Q5qVvDol0VbGMIMxjoMyC/N5XF6del/n50ZDXGyNVyxeXVkvPzBet1AxECAUQEF5ASrDGUhaEqDZOqwAdHjDGH0SqN1jqrliLX1ZRKEWOiMBYlJdVkgnMtdV0zmUyRQqCVIolsDiS1yYZKQqKkQopEDA6lFdVkymLlCD6gpCClSNOsUcl0Icw5ITOlgNYqq5tSYIxGqaw4Kq1RxuB9YL2uKUxBUWiqaorSBiEUxliEELRNQ1VWKCnxwRNjQEiB8w5SpCxLtNGklGjqNVIplLao5IFA8L5TLAUuZiOm4M22/3ble7wPpNgQfSSpEqkMSSqEzOVWmtYRwrZmaEyRoiwJIW4mUPYnHXIo/FOerUEX5Rm2ez/oH53dD8Nnb2/756SUjvhkI5nE13zTO/yKl5+tJunvfPvb+PM/+k8BYH+y4vV3v/ChPSMjRowY8UEh2ff2rgNokuMX/eCvZ/V37ozvuhHPBS8EKQU2tRWvuXZuBu5syOR+eQr2lsGBQe0gjFHQEdL+eMMY3ZQQYptTOrBo2fx/Vx9N157bfI7rKu2O620fAnoDBHJQ5oWOuOyTysHqwfIUAkLKDRnpfw/V2X2ikkNbs6nO47NLHp1f8ujhZQ6hFZIQfS7YEQXTScl0UjGdSKaTgumkZL1OuNZhjcVay2QyQevcvcqyJMZECJEQs/HOyekpj8/OOL+85N7pKVZrUmgJ3cyDtjYrpUJgtURLwXJZY7RiPj/i4aOr7LirFSkFFosroi3Qfehtx9RtYbqapwlbWgpj0MKgjUUbS9O01EvH0fyIyaRkNjtCKUmMUJZTfEecX3npFmVZ8ODdNxFElCQrtSlxdHSE6ErjLBdXKG2Yn54itUQQaL0jeU/dtiQpQUpKbYjd95XDhRXOeVz0uLimnCuE0h0plQgpWS2z4iylJMSAC4GqmpAiuTTN0FSof5YOTeT0z8ANSuow3JcbttvvP/vP2/5kyOaYYrdJ2xzy3X2fV07piE82UhH5M9/8p7inpk/dNqTIX/zeX8DX/ztfeOq2I0aMGPEi4b2863o8Dg13fm8J3zeaG414PnhhSOlNhHQz+E2AvD7oPmTWctPxoCOaXX5kJlthc57t4LsLWOhddRNZpU1ph8Dmth0aZB921k1xSwxjjFkLvXHgPQzvvSmEF1KMXcjnluQOFa8hMd2vLSk2Cmxu1/b6FUJYbp3cZl2vWddrZsdzlBT4ps2kLTiEzIZCSmWFsSoTk8mEFBPr9TorpFJ24buREGI2P1KSpq4pbMGrr3yGdr2gbtYUSuB9oPGBi6saYws++9lXaVZrfNvw6iuvIAU453A+q4az6ZQQI947yrJAS4VwUBYF02mFIOJ9S4oFIUScaDFFiZCKkCIiJ+5SlRVaKZZXSwqt0FIQnMdoxez4iPvvvEnbNJRWURQaU1jqpiX4QB0989mE+XzKo4f3cW3DYl0TnCf4yNGsIgFN63KJGq1pmgZjLPPpjCakXCpGiNyetPF6JglFkoooJEcntwjec3V5TlVNmM0L1lcrvPe0rt3JKd3pdzw9lLfvOfuRA+8n3/RZzpUdeK89JZv9RkI64nnij1+8zJ/4Pf8i3/Ajj8bw3BEjRnzi8U1/63/JS3+qZPajPza+80Y8N7wQpHSofqY+JnVTGqLfYvNhd7C7WfXsYQapIwBDYruj/PRK54aIbs8zOMihP3O7N3+LwTW8R4jBHzvRw1v9tjvdJsJ367R682GzYtqT0W2abSLX+mw6c6CmcVhj8K7FCXLtTiURUaGVQCqBkrpza00opZBSUFibyZ931867If8I2qbNuZXTKb5ZEYJnUA6TEDw6arRWONkrzJJEwrkcDiulRGuFTDLXR5USIXMYsNYKrTQxOEL3ho0x0rpEYSMxRVIIEBOChDYaIcjtwiCUzHU/OxLdNjX1ak2hp3lCA1BKd0HWEal0F/YrIQWc88QQu/IsW7KZPYy665G55mgdWkKM0JVKFAliCMTgCSHmiQ+Z0Noiley+b4mUuc6q836jdO9PxqSdvnR4smTn87Vw9rRTbui9ulnvRDr0DTrAN4fk99kI9IgRHw6+5+qU/+RL/wNu/2c/SHDt03cYMWLEiBcI8cgzvbW+sSLDwX3+yZTqL3xhJKQjniteCFJ6HV1Q7SblTmzZ02AT2a2PvZL5NMQubHFTk3O3PucG+3VHB2ceDtDpyG0+QFbdZLdRQnarBNvmC+QOZX0CxPbY/f6ChBgM6lOCSK6lGkOE7nUikGz59fXQyN5DRkpJpmQCYuL8askb7z7gp778Futlw93jOVYEohaEeg1KUU0M1mqKwlBNJyhjqOuaorBoZShKi5SCalLgXcA5x/HxKd4H6nVL6x1t67hYXHF8fMTR0Rw/mdE0DcurBVVVcWteUteORGJxcY5AoLXiyz/1laxqTiYIY5keHVHXNVoqptOStqnxzlOVGpGgXrbE2KCtJknJumlwTYMSBpEiodBIEkqCLQwhei7OL1H6CK0LXHSk1iEWjqosKQtLaVUum9PC6eldtFa0TY3UknWU6HIKztHULZOyoJxYWu9JKaBwSCxSSuaTCcIYgoLaO5o2oMuuPmkStFeXuNWK6BJCaYRSrLQGIYjSsGga/GLFxfkVq8sFYb0mOLdTzmUTrp3Ymak4RPp6AspeX8mLthL8pgbqIBR9/1g3mWpta5tuztr9DoN95SaUf8SIjxpNcvzh//3/jDt/5YvEkZCOGDHiY4jf+gv+Bv+703/ARD576O6IES8CXhhSeihPdDi47UndYKONWdG+Uvqk2qb9cdKBUNzhdn0I7HWH3X7fftCeNtv2J8jRxv1gfHCOjTr57KGJw7zRXhEliYFeKrpw422+Xs+Vh4ZIG36yF9Ybuyb6JLlcN7x1/xHeZ+UzxIBSMKkMQutOmRRMJiXT2QRtsrTXti1SCpQE7x2ic9/NUaiiCw3O6qQ1BqUV67YmxshisexKpmhu3769MUg6PTnBhUAIIeuMKeF9yKQ6BAQJJcjuvDERfaIwGiUFWktCgOAjtijQWrJaraELXzbGUBSW+WxG8I4UPW3bkFLCmgLTGSEZY1Eik/rpbJpJXvD0FVt8p1C61qFQaAnFZIYJgbRegxA471HGIoVGJkVSBgS44OknXpTSWGtAKhAJicB1ymeMEWsVRVURpcycNUSMkCipmVSO2NUnlR2hC500fE0xvQGH+vy1frh3jCHZvOnZ2w0T3+4zVFyvpX7fEHY/YsRXi1vf8Jif99JXmAj1xO30OhJXq4+oVSNGjBjx1SHpxLf87K9wZGoAvmP6Y0ykfaZ9/2YN/6v/8rfw2n83aqQjnj9eDFJ6gJDu/w0cij3cMXN5lvzSa0YwHYbqzD5xe9Zr2IZK7g7WDw7ybwhRPGQY05fH2Kia3afrJGGTlbfHQtJGHR0eP8YIUpIENAEuljVv3X/EXE+wxuJDwBqw1qBs0ZF5z2RScnw8x7uGGHKoqlISJQXOOYQQhBCRQnU5pxLnIMZAWRYgJat6nZ1+rxYURlNYy+1bt0gpEULghFPqpuHs8iKT/LS9VzFEREpI8g8x4NvE9GiOtYYQIylFfAoURYFSkuVyidWawhqMMZRFyWw+p61XuLamaXLtT2sLtDZopRDGIokoGZlMZxijaVfLzSRAzuOMBO8wwiCVYDI/JpGIJHzb4nxgOjFoJZEi4snuwm1oSVFBFChVorXBIbtChwIXt8RSa01VVXghckmY1qF11398wNc1SWSH3hxOvTVxP5hXna6Twb7b5E5yYN2gPz45V3S3X++XPupzmm8q+XLdPXjEiA8Gv/7z38+/efqPgfLgepcCF7F9n/kWI0aMGPF8kEziP/r8n+MbTa+MPnnirccqtvx/z34R3/Q7fojUNB9eA0eMeEa8GKSUwwrJPjlMw4Fsx1QEmaQEsrq3f6x9peZGA6SnKDRPdfftTWr29jlEkHeu6cA21+qr5qUM2UJKXYbp5pogxdhtpfb2T7u1VcXucWoX+Tt//4e5WqzQuuT4uKDQkuViTYgK30qkiVijmB8dUZSaFFtmswkkaOsaErg2cHFxSVkWzOdHGFOglaaqJgghca5lMqvQ2mBLi3OetnUYpRAkLi/PqeuGpmlxwRM7w5/FcsW6zmVZCmuYVSWL1YqmjqToSTFAitT1Gt/lsgqRa4LWdZ1rqOpcgsU7h/eeuml4/PAMayRaG6To+w6sVzVtDb5ZUZaWk6MpP/3GG7i24fT4GCUlWgli5w5cVAWkSFs3pFkXLp0i09kMYy2thyhAGkEKgQRU8yNAknwOwU5IlNI5DzUl7ty5A1JztmhZrde0IZC0RSiFtQUhRoKPrK4WrJYL6qbOJWVuUDB3cdgxejOlsa98PmGy59qRbzjnsO89aZJmxIjnhW/7/n+Fl/5gSfX3f2LMqxoxYsQnGk1y/MLf92/yyn97RWp/5Hk3Z8QI4AUnpcN1cE0b7FfeGJp4iJg+6fzD38+6H+xYBm3bdcM59gnywfN0iue+sczw9qTuf7umTykrZoPzHSL6wzb4EGkaz8XFFU3jUEkgUkKkhDEaLRVWaYwWGKMoS4s1GqPlZhLAGAOpq6tKJMYticnKXUCIrLj24buNp6sbapApEmPAtdu2xq50jNIqGxS1LaW1mzsdY8SHwCDbNk8MdGZIm3OnRIrdtcZA9Cm797aOpmkAkwlsaTYhzyllp2ApFSkl6ralbfM+Icas/gmJDy0CsMLmEOIQcE2d64qm1IU751qjCFA6EYTLeZnSdGZaCQLEFAmiC8OWoisDI5BKbUyokggokcvHEPN369oW77Krr5Bb0vekCZhn6af997fpeAfCcm/ad1j66L1iJKcjPmjEKmJPa141Z0/cbvHujFf/+vePhHTEiBGfaPz1teTPPv7FvPS3l6Qf+OLzbs6IERu8MKS0N2i5ruTtEdFeuUnshO8+qW7ik9TRp+EQMR2WT+nb1VOyrTuuOHiMJ4X0PuncvRraGycNhK3N8dIT4i4P3VMhBItFzcWipll7og8YBMuzNc5q7n3mlEmpmZQKHzLJmlYFZWkpCkPrcpustcymRxS25GpxRkqR1WoFSZBiYrFY5vIn8xlFVRBj5PHjh8xnJ9w6vZfrb/qW6XTKdDojJbj/8AEhRkxZcH65oPWB1XpF9BqdIleXC5Z1jbUWITUiBiaTOUVhca4hJUmKEiUtiUjrPW1d49qG+XQKIVIqjXcNrVHcvvUZjDHECK6pScFxPDthtbrkzbfeZD6dMJmcYKylsIayLFi+u8B7j64MIkRE8JzdfxulJLNpRYoJFwXHt28jpKD1NaKpcwkXL5EINImmXeO8p1Yaow2lsVwtrkBqJtNTQhK4RPf9CqTWiJhIONbrK0JoOTk5oWka2ralbdtr3/VuP7geIj8sD7TXCw8e5/1iPzpgzB8d8WHj7mtnfOHn/BnUAQO7ESNGjPi04Tf8td/IN/1rfw/hf+h5N2XEiB28MKR0Syo7A6JDdrpdyG7a/A2JSC8tpkF9x02eaUwDfrgfYAvslFjpN5TXNFkhJJtczc3m3SA+9VR0P9Q2X4vormfrIgyJrPL1Y/IdQt4TbgbX112yQGxvTdr8r2/l4IrS3t9pU8oE8iSAi4F33n3A4/MFJycl7dpRXzboQmOswjvPOgWcE8yPKqqq5M6dO7R1Q71qQOSQ01ybNIfPzqbzzfGNNighMEqhhCCERNu56s4nRxitadya1eqKGAJVWbBar1nWa2xZEGNi3dRMJxVSKlaLC4xRnJweg4JqZTi/WiAApRRCRISIGKORItdPdb7Be0+Mbb4HQlCUJUVZIJRAaoXSmrpuiaFXh3NY8+XlGTE4ZpMZZZnzQlerBZIp02rCyfEx3ju8cxTGUJQzVssLXAisWkdlPCpGXLsmAY1rOlOjgjaZrj8mAjU+gUagRadAS01C0NRrhClQtkQbi9IGrQ3tusWtPVoXKOUJboUQoI2mbpo8ybN5ltJG7ExJHMwn3eZm70+aCOjU503n77rcTs3d4aTH5lG6fq7U9dn+VH1fToLrUyqjaDriA8KTCOn3N45f/2d+G699YdRIR4wY8fHC7W96xHe++hO8pN7DpFsUJO8/vEaNGPE+8UKQ0m4YnAewojf1kddEmy3p7PfbDrr3jzgke6S+/MnwWP1+Q9LabdGbFQ3yOTPl65Wk7nN/jp0jC4aD8d7lVwo6YpqvMTsKq2weFHeJwCa/Lw3+HrbwgLiU95XDqxiEPUMgoTeth5ACrW95+OgRDx9d8tnP3mOFoL5oMFZjCk3wnhASNIn5yYSiNBwdHXHmzmjWC4y1GCWpyorVaoVzLaenJ9noyPtc1QaQOhObEBIxZvfaaTUhkGhdzWq9IsVIVZasm4aLqyteeuklUkpcLq6oypJJVdGsLtFacnQ0Q4iINZLzy0sSIJVGiDwBoJRCa53Diuu+fmcOjVVSUtgCawsQIJVEKkndtqSUMJ1hUwIWl1copZhMJliT65Eu6hWltUghmU0nhOA4OztDFSVlVbJaXRFipPUBEyLRB9pmTQSatmU6O8baiuC66i8kgpAEBKWQ6C7sWGhDTIL1eo1WGqMkurAoZVBSkwJ459HKolRL9A4hQGm9fS72+8Gm8zyJ7aUDBPNAaHr/qDwprFcM993u2E+u9NbZWxLLzr5jKO+IrxbJJKx6Mtn8Yv0a3/B/+1HC+cVH1KoRI0aM+GDwyz7zY/z7974IVE/dNqTI22GFcOO/rSNeTLwQpHQnNzJ1ZDMeGlRv1cSNI+1T8j6H4cA9Qe3Hw+mm8XnaqpNbvWgb2piIvXzKQYZ44AJ7haonmaKTioQQ24KrxI25D2k76/V+Qx3370vctF/QuMj55RofBAKNWywRHqq55eTWMWVhWNdXm9zMet3w2HtWV2ussVhrQQhCCCyXS5RSTKdTqqrCWkthLcurBd45jo+PWdcNj84vMEaTElxeXmEKS1GVrNdrgvdMqwllUXL3tkWiEFJw7+5LnJ2d5e2NQStN02TFcVJNuXfvHt57vPcURYlWisvL3G6t9aZsS4yRoigojEXp3O1DCNT1GtdmIkqMFFqhZMRIyee/9mtpm4bLy3NCyHVoq6pCCsFqteDq6hJI3L59C+ccDx+dYYxhMp9x9+5d3r3/iK+88Sa3X76HsdmdV0qN1hYZPd451us1Ukomkwnz6Zy6bbi4uKCYzJHaUlZTolC4dQ1Ck1SiDRKlFZP5nHp5hZQKZSwhxO7eqI0Lbxg8J32fOJTbvCl9JLjmjJufoev8si89A7sh7Tmz+GaklLpawdkcbOMaPUbyjvgAEYvI//1/+D18W/EWMHvezRkxYsSI54o/vzzhP/nNv5Gf8aU3GHXSES8iXgxSyoBw9fJjr0jeYEC0//umnMmd9Wmr0txs1NKfe6cV0Id/ibSz7U18+PDhBwVdeqk19SoeDGq6bOIaD5GI4bVdP+/uiQ9tF0KibhyPzxc4n1BSI1N/nV1BkxSIMWCtpSxLhMhE3doCo3It0UQOm825mLELk821NUMIKCUhaeq67vIcs2FRSvn4wXvagQ25854QEyElUmyRUlEUFhJdvU6DUmqTM5nVZoEUEq10F2J9wOynu6lKKay1GK3RWqGlQCuBknJDpK21KBHRCrRSeNnXgZUd0TVIJbcTDAK0sfiQw2WltkiliSn3GaF0NloKCaEVvnU0rAlJEDdlXyDGRCQ7+nrv0T5kRV108xNK5D6RRHZZFqIrteNw3ncR39dLH13vHwwmR3ZJ6X7fP9yvUhdcsPds3YD3ZhY2YsQHCAk/q3ibz5uRkI4YMeKThTiJzF++4uvLd595n/MwwfzQl/FjVMiIFxQvDCnN6kxCbFTDJw9T90navtvoIRLXGwVtCTAH1M6087s3GFIHyz71uXoH5dZha/f+zOeMMeyZM8nNfqIjQU8jGU9DSqlTSPukvYRzkbOLJT/xpTco9JTCFFgFITicb1itLvFO4X3LfD7l3r07XC0uKQrL133d17NcXLFaLBAyl105Pj7m4cOHLBYLTk5O8N5z5T1HsznWWr70pS+htKaaTbm8vMB7z2w2w7mW5WqJVgqlFKt6Tds4XOu7mqEWLY834dfTyQyR0kaZTQlWqzVSKsqy3NzXqqq6+ym24dNS5vqkZUlVVVRlQaEVZZGNi45mU6qi4Gg2hehI0bFeL2mampQiSuXapSSJNQZrDcUk1zu0ZUEkEVLE2oIkBA8enyG05fbdu709EVoqrq4ucf6c4miOkDnMeLWqCT6htKNts+FU9J6EonENRVlRWoOUGiFlrjkrQKjE5dUl68WSEHP2shAC7/1A/RTdhMqQsG77Z78s54V2Kwehs7uTPXHQP8XB2r6pz/ne9PPr2EwQ0Ye+7+aejmG7I0aMGDFixM2Y3lvy937enxwN3EZ8ovCCkNKB4jkIqd13zR3W2uzX75us3Ojc26s7aTAAF4Kcurrnzptix+G2jroCOWjXts37ZkW9+cs2iDGXGBFCklIejPdNFDvH6wf9G8rahfw+w7X1925vMH/NjThGQgw8Orvk8mpJShrXeqILnMmsmB7PjplUmqJQTGe3McbQuoZJNcVay3K5ZrVaU9c1t27fRSnF5eUlWmuOjo5YLBaojgD296OqKmxhmZ8cIyW0ziGFQGlNYQumsyk+Rt58+y2KqmI2t5ydPWZV1/gYaVyDEJmAFlZzNJtt1FfnPNbqLnQ3IYjEmGuV9t+FEJKyLCnLkqIoaNoGUkJVBU5mhTjGCU3b8vhxQ87wDJmcpoC1Gq00Sqqu/wTW60VWl4VkcXGV+1QUSFMgpCB6gS0qrK1IrkZKck1UU5CQRGPwAdrGoZVGSsGqbtBScHx0hDITUAYokFoRgBQDUggKY2mbmrpeMT86QiJ4+O5y42CtlNqGt4tOYWUY7n54omMb3H0o6mDbM0U/wfEe5kneTwj66Mw74v3itZ/5Dv/Cq1/k1cOziRt8/r/4Tdz+PsOd5d/9iFo2YsSIER8M3gshHd91Iz4OeEFI6TbXcvN58/9ddee6WcvWWTTjhrBWEnLAKvsjpNSrNcMT97mn/SD8+jkHnHTQ/n7Qv12x9SxKXbhu3r8vwZE3TTv5rmnHZGlHXN25nmEDhoRYDNYk+kIiWTWMIXJ1tWS9ahBCEUMOH162kWmpmZUVhRUUpeb05AQffK4RWkww2tI0Ta6N6T1a61xWZrlgUk2oqorFYoGUEilzeGpMCm00xhpsYagmFdrpnI+YBKCYz+c5BDWBsZbJdMrj8zNa39J2Bj5CSJxvMFFhi4LVak3bus13L4TsjI4OhaaC1tmNV0qJcx6JIFiNDxIlAylFgo80bU9KI0YnlCTngwrV3UNB8IE21GhZIATUqzpfs5JZzVQSkSLGFhRFSRAeKRJKgTW5hE2dFDFlpVwqDVHS1i260FRlBcoQhUajQUmSgBAjSeQL9iHinKMoS1zT4n3o6sPmWq1SksN8EaQDz8tBRjnoUruTHHvEtA+Bpw/7PXCsAxMkT60VzE1P74gRz4YkIRWRX/byP+TfvvUloHzi9q98r2b+PV8Y05lHjBjxsUEsI5V1z7TtWVjxZa/5zF9WTP8/47tuxIuNF4aUys6RdlvhpWU7RFVdSOGWpG7qLW5MibbhqUBHePaNfrrcTbld1Qcj7iANZ5/yuhgH0b7D7RMg4nZJiqQkOwLTbStUt2HcLMvN3w7wRSKbHG2q2sTB8fswzMF5+xhOKXeU2m3VmY6KbIyVPIFMwt595zGtixxPSoTM+0TvUVqBaqkmR1RVmQ10ksAawWq1pFU1VXkLbQ2IxOOzxyidS8JU0wlFYTFW4dqW1WrFw7OAlJKLqwu4hAcP7zObzSjLkru3b9O6ltV6xT/68X9I0zqqcobtiK42lhQTKQVkl8N6cjwjBs+DB495+PA+67rmM69/Hte2vPPuG7x055SqKDBGdX0E1nXAh4D3Adc6Fqs1L9+5i1KaOkYmtmAynRJ8QlvNnbu3OTt7SL2uKcpJVnKrCcvFJeu6ZnH1GEFAyoigRgiFKSxGSwoyGZdSIwloqTBGoUwJyUOokfYIaSv8YoHUmuNbxzx6fEHd1GiZv+MmCrxvCanB+wW6mmImM1LM/cbHiDIF5VSwvlrTtI7lMofwSmVQIZFiyP1d5P6eCetg0ufgv0zDiRUxmGAZ0kWxCQveCS8nOzz3ob+HjJSGiINjbk7RTxaN4bsj3ieKV5f8pZ//R3lJaZ5GSEeMGDHi44ZkEr//f/Sn+AXFOzyLgdsv/Xu/gZf/rZb5W198ogHhiBEvAl4YUkpKA2LX/RZ7A9cbVMle7dwJO+yOCXthr93AefN32iV7GwUyDc7dl205mCc3VHP78/XhwGm7yd6uMXYK5oAcbFWtbdv7QXoa3p9hW2PqSOugOWJ7jGzGk1VY7wOti7RtIMRIUQhMYZBS4FoorKGqik5VVFhbdAZGOWdTyXyzjVIYVdL6bNQTQsA5h5SS4AMhREKInYQpqesGJSW6LLvSMY6qqvAhGyMhQHWmRt576ssLBGCMRWuB8717boV3glVKaG0oi6yAxhjQnaNuShGptjmLWmeC6l3AOY+PkfV6TYoJKRK1tRRaowuLD4K2bdFKd6RcgsjfST+/oLWBJBEikJIk12o1ZJFaEJ1DICmszbVTJRiliRF8EOSiNRKpDCnJ3A+E6ErVmC70NhG7707KfgKjy8Ds+5iUCKlomhbnHNZaWh92XKulEESx+1zcZJz1NKSd52F3XT9BJK710OvYJ5xi+IyN4bojvkooFfm60dhoxIgRn2C8ph/zin6299xyXRB+8sc/5BaN+GqgP/Mq7/zKr+Hrv+GN592U544XhJTu57ZtQ3Y3+kxHcPq8y/2yFXn76yT00Pr9s15TcnZI767ZUB8iu5trt2ewlGAreQ7IJXtE4BnH4Pvt2L2ASG+K1BOXmHaJQ0oQk6BuPKtVDvUEkAKqssRYQ72C2bTg9PQoi2tSMp/PCSHgvefW6RwBPH70iLIoqIqCq3WD8z6TvJRwzhF9IIRACAmjM8FdLtZMqpLqtOKdd97ZEFilFUJKppMpICjLKfcf3uf+wwccH92mKkuOjmc8fPSYxeKKoriFkiKrpifHJMjOucZydHSEEJkgK51V6hAiZVHgVeCqXeJDi28jZ2dnlLYgtBUyJVIImNunJALt2ZLT4zlVNaNeL0kp4nybw7+VYjo7IgZPCI4Yc38oywmCiEwBt14jUuLkzm2k0QgJRVkSvMO3TZ5ASaDtBN9G6lWDFgJVWGazGT5Emqbt3HsFRVGAUvlzH4otBLJTIxeLBU3bcnR0RN22LFdhOxkjJWJPqXxa7vHh/jfMf+4J+i7R3Uyp3HCsa/nNN7TlWdozYsSIESNGjBjxScDqW1/lb/0f/yATaZ93U547XhBSeh1pQOZ6xS/hd8p93LjvZp04sGz3c+rUz931ewmcAxwiw9sc0f64cTNoz4d/8iB82KZDJV32QyCvkdouz3Bz7F497vaLgEPy9oPHPHpwnpW7FFktFsznU6xRBJOQMpKS4+pqRYyJpmmYTqfMplOiD2glmVUlgoT3Wf2UtqAqK46O5lRlxcXFJSAoCts55Ca+5ms+l512lys+//mvxVrLxcUFWhmKqsS1gbb1XF6eYbTk5Xt3ePTwktVyQYgOrRWnp7e6eqaumxhQxJTzKiErpkSHc576asV0OuX46Ihm3dLiaIsCnXLdTqkE1mpeun0bYzSCyGQ2RaTI6uKM1rWoTm31MeB9S71u8M7jm5r5fM7du69wtVwQY8TYiuRbok8QPARHjB5jS8y0wtVroo9IXdD6SPA1UZU4F1jXLZIIKXF5dUWMiRAiSUqkUl1/l0gp8UBMCec9WivKsuLo5JQYIm+9cx/nAlqr3I4EbIzBtkSwVzUPOVXnLrX/nPQdTewsG27XE9U0eA56Z96bnlPv87Os9oxoxtDdEe8HSSX+pf/+D/AdRz/2TNv/mp/6Z/nJ//SbeOn73hzr9Y0YMeJjgVe+5T7/i9f/Nl9vwtM3HjHiY4gXipQOB7ADK6KN8hNTIkdUHgo93F12yEH0+jnYH29fC5O9SaXcbUO6PrDvSeTOGFtcI6aHBu03lbXp0RNjsdVeSUkgZB+KnGtrxtjfN2gSXC1rzi6umNoJIkDrGiAiBSgJUiRSjPjg8S5sSq9UVUUIAUlCKUmKgRQjWhmEzOVcCpNrfBqTQ1Cns1lniBQ4OjrKOanNmuPjY6pqwmKxyKGxqc9BTDjXUhSWqS14cP8xPmRiXJYV2mjadkkMuVxMjD63NWaSqtVWwQ4hIACrDV44FLmmp0AiASkkSkkmZQmdOVIOTc7fj3eeVgpUF4YdYtwonN5nJ+Wiqli1LYSA1oaQAtFv5ERiynVJtS2ol0tSTChtaX3OCQ0p4nzEh4hVff5rTW9U1OuiMUZk6lypZe5PkZ4EgjYGqRStc13f6koJ7eR+7hHPTvm81hfZfW5uRk9JB+G871HcPNTvR0I64n1Dwq+79X383OLJM81NcvyN9YS//cWv5xv/n18YCemIESM+NviZt97mt568CVRP3bZ/17VnY279iI8PXghSmtK23EtfV3I77BbEkGeFhEybbXvk/eQ14nhTuOAQAvJAn60amVI2iYFdtWdIFJ8UcrglqT2X7rcXg7+77RJPpACHFNJdUp0NlrKDbsrFVIUAqboaqLmszNpF7l+1rNuEUAXGWKRJVFaRQkNTBworUULQriOvvPQqZZXLp3jvcc5xcbXoiFugsJbCFpwc3yLGyPn5Oe+++y4xRk5Oj5FKAQHnc9mWlBJlWXD8+udYrxtWq5qjoxMePnzIl7/8j3n5lZeYTCdUkxIlsg/V3du38TGhCsvjx2cslwtOT+dolb/rXJZmnR1qtaYoDLPKMp2UvPrqPYL3tM2aZr2ibR2t8+iioCwLZMy5mrV3FEZjpOT+229RWMvRbMbi6oKzs5o7t08pi5LJ7ITitkYKaNYrUgpcXp1Tt3U2ZSo0EoUIAl0WyKIgKgOyAGlpW4eUivn8FOUTjYs8fHxBDFAYw2QyQUq4evstrC2YzeZcLpedurxEmIA0gcnJbbQtkGXB1eWCxdWChw8fUS/XzGdzrpYLQh12+qpSCjGYWOnLxjzpudh5RgZ51Ju+KCDu99yOmO4/m8OQ9xgjUubvr88BHjHio8QX6oLf/y//an7GT/0Yo9YwYsSITyrGd92IjyOeWuRICPEnhBD3hRA/Mlj2HwohfkwI8cNCiP9MCHEyWPfvCiF+Ugjx40KIX/7sTekDAAflUTbutN1PEjlVM6btTx+i2ocQbhdf+4Hrn/OHSIrbH+gdQbfH75f1P9db3v0M2kHnwNufS+w0KG7DkveIL2Q1LKZESLG7ttSRzOFPIqa4ofCxuw8xhHx8IiFB3QbuP7yiXrbgE65tCMEjjN60eT4/opxMEUpjigJTFhhjMFpjtKawJdoUOJdwLuFdpHWREAXVpMQYjZL5etum5fGjM5q6hSQobIkUkrpec37+mLOzR3jfAgmjNW1T09QrpJBoZbDGZidgEnXdoLVmNpujlEYI1ZEahbGGojAoCb5tchQzEucCUiqm0xnaaKTOyigx4NuGwhoKa4mxM2XyCa00xhgKW3Q1TSconZXgTRh0iKxXC9bLBfVqiRaCwmikiCgjKSqL6CYGUoi06zXry6vsxis1zoWsjsZEUZQYYyAlXNPQ1g2FKTBKQwJbWIqqxBQGpRVJyM0EQfABgULrAiVzGyN0/Td0DsCCLqxgJ3S3L9ezP7myeeYG2OSKCrn5ybHhu1EBqevL231uJrq7ofW7P0/LCf+w8dG960Z8kFCvrPiWb/0Kd1X71G3bpJAPLwiXlx9By0aMeHExvu8+2RjfdZ8M/PnljH//3V8C7tlr0n6c8SxX+V3Ar9hb9l8B35pS+tnAPwL+XQAhxLcAvwb4md0+f0QI8eTq5QDdwDbXtYxbV9zMqxCkrPZEiYgCAhAidKGNOVo215DMIY/Z7CfGNCCF3fr9zzFtBvMpZjLXk8cU82Bb9D8MCXLqyq2wSyzZJaSb37EjojFADBsDmmt3YnOsLTHd/N4jpTFmF92QUq5j2eVMhhBIKSBExCdY1o433njE8rIGF2lWK1zbIozd8JDTW3eYz09QxqJKiy4sUkqMNlS2YDrL5j/OJdo20DSeq2VL4yPzozmzacWksBAFq0XNW2+8zWpRQ5RMqzlCCM7PH/Puu+/wzjtvU9drpITptGK1WnB1dQmJnGdaVJs6p4vFgrIsuXfvHtaUuQ6oENiiYDKpmE9LCi3xdQ0xIZJgtcqlWk5Ob1FMSrQ1GKNJMdCsVlRFwaQsIAaCCziXnX0n1YSqLJnPjzg6PsEWFULpDRlsmprHDx9ycfaY1dUVhVZMiwKRHMYKynmF1JqEIHjP6uKSi/sPsuGTsqxXDXXT0nrPZDqjKktiCKwXS1aXC2blhMIUpBipqorZ0ZxyWqFLi9SatnU0dYNrHFoapuUcW1QoZQgpEaInRodUXSi3lNdmULbEVG4+79QjTdtttuvELintiemgX6cUN9sPSeWhv2PcJabb4z5Ztf0I8F186O+6ER80vvNrf4K/9I1/mdefwY0yPtM/eSNGfCrwXYzvuxEjXmj84a98J//53/y5yPWn49+up8bQpZT+phDic3vL/urg4/cBv7r7+1cB35NSaoCfEkL8JPDzgS88w3m6EMOcvyfSnoqDQA41yd3Ez03YbM8K06AUxiHDle3n/phPbluP/ZIapMH+25jd3VIufVmRdEhJOqwKbRRjuhBlnjyDsL1GgUiCkBLEwGrlqOs1Snnm04qjosBIB1oirODWyS0mVclyuSTGHLJ89ugxF0owtWWuhxoTbYhorZlOp2gpUVKwXFzRNppCzYghoZTGB48xinsv3UVJSUyBy8tzVuslq9WKV199tVMiS1arNSFElBZ453njjTcpC0tpLY8fnSON4XOf+xzn5+c8ePAA1zYoKZhUuXRM61ouLy6wxnA0n4MQ+BiYTCcIBFdXV0wnU7TWrO4/oigKqqpiuVgggddefYUUMrkqyxIQnF+cE2IAEoXV3bcTgUzkjm/dpjCGaVVxfn7OctVw6/YRlS67EjotIXQKrzEoo2kbRwSaxoPJbrqPHjzMTsXOE31WNyeTAhcCq6ZBySKrtEJghEGLAmlKQOIjrFYr1suas7PHrK4uaZpmEwLfh9AO1c+ha3Sec9nt81LKrs+Fa2HjTzMWexIOm3vlfrqP551T+lG960Y8H3ztn/tXee2vJqqHP/S8mzJixHPH+L4bMWLEi4YPIrHrfwP8me7vz5BfZD3e6JZdgxDitwC/BWBe5jDGTfjrHk/szYfSgJQKMczhhE4u3ZK/DXHt3UZvav6TSOkgf3Ogig4H6Wl//268PQxF3G0/B49z/dR9vPF2v3zom8h1/3cCZKf0JpqmxTuHVmCNwpYKIxNJQlRgrcFaQ12vycTL4HyDCImgTA6JTWnjlloVJVrKXJKkrYnBU9c1kv4aQSqJ1VlhDMETY6BtW7z3FEXBdDrN5kS63ShyiEy+67qmrWuca7FaY63tjI2y026UAqcFLnic9zRti+rMlvJxBEoqErlEjVYSrQ3GmFyGRkq889vapp3BkVIKUmDd1BvjoxQjUSSIHrTqDJI02lhMUZFEdssVUqO0RZsS5RORkJVorZD0YdW5RI3UmSh650hdjVKpFFJA2zb4TnVsG4cICaktqO4rjbl/x5jwztG2LU29pmnqfLwUr/WJHn1+9BDD/ic2pYzETj89dLynkccnGXkNJ2P2D7OdsDm8/gXAV/2uU6enH2b7PlVIOsGx4+Xi2cLTTv+BpPxLX3ivnlwjRnxa8Z7fd+O77sNB0glOnv1d91dXhv/3g19I8qOV24iPF74qUiqE+PcAD/zJ97pvSumPAX8M4OWjSepVnpzLeZ1sJdJAKcyEqyeUidDvtPlJQsFmIL6rdPbHfELrdvbpw4u3IYaDgXd/PtK2/Ygc3Tgkpj1p27uu/QH+xoymz22VOT+xD2vuzWuG597s2+8jIBEJIXF1uaKpHcfTAqk8jQ/4FBBKogvLarXEO4cQua6osYZSa7SSHB8do5VCK4WPmRIbpXNOpjGUVUnT1jx+/BjdOeDOT0437WuahrbNxLM3PFqv1yilurqighA8y8UKKSXf9E1fz1tvvslbb75JNT1CSsH9+/cpy5JXX32Vt958g6ZZc3Z2hk+BRGQ6m6OVYt00VNMpRVnivEMJgVaSVVMDcOfOHZqmoWkaqqpEKc35+TnTak5VThBC4EJgUS+ZFAVaaFxTk0JLWy8o7t4DU3BxuWBtHG2bOL51h6IsOD45wmiFNgqhDeu65ny1RBqDEhJjiy50XJG0IUnF0fxoI/hrrXGu5Yd++O8ync25+9IrvPPWm/gId156BWksQjUsa4eQmqPjU4jZCXm9XrNaLlmvFgixrWM67OM3KZ7DUNvtpItAdE+a2EylXDdHehb0ffVwGaVD6J/w7bP2ouCDetcVr782cqIPCPpOzd/+Z/4oM1mQZ25GjBjxQeD9vu923nWvje+6DwrqTsP3/+I/8szvut/9H/9mXvlPv0i8uv/hN27EiA8Q75uUCiH+18CvBH5p2o503wReG2z22W7ZU9ATu56AwiFLoXyWtPOzJYvdfhsFs3P+FHLvGJ0tUBoec2+wLfpj7xJTgBjDwE23j95NG6WpF5yGyuomdPLAHH2vbm3z7eJO2GUKPQEf7LMJzxyQ3Mx4SSkRRD5GiInWedrG42rHxEyw1uLbOhOPZIgBggwolcumlGWJ0jkd0TmH7+qAKmVQWqMKvQkRTQSUFFRVlXNlO5IspaAsS2JnuhNCoCgsxhwDOfT06uqKlDKxKopeDfWbNoQQSM4hbWC9XiOEyGqnAKMEq2ZN6x0xJlz0hNbjfTYu8q7BGoWSNiu1KSGFomkalssllS0QKXF2dkYKmYQtlwkIGKWIweNSRJTZuEjbgnXdIBqHALx3LJYLiolFB8VyuaQoLEUquLxcZJVXWbTSKKGomxzSu17VmHKCNJYYshmTLSxCSJKEV159jZSgqfN1pQih9cQoSAqsKVDaomRnriSgtBZvLU4pUgqDfnkgpHxDLCVS3lRzt8/zHPb6/T47iE7o9jlEVnfC169NAm2jF7ZGYl0cQOqMjw6c+3ngg33XjfjAIBIzWWCektr2xy5e5f/63/xKvuFH1h9Rw0aM+PhifN+9eBDP+K7roZpEvLr6kFs1YsQHj/dFSoUQvwL43cB3pJRWg1V/EfhTQoj/CHgV+Abg+592vG3Y7pC2bQfG/aC2d5ztQ3chdQNrMRx7D44rhkaheVnqCWe/YOv8mZWjTYs2hDG3oSe6dNUut6P2FLOiua3XmDbhqNDn8+2S3O01pZ2/t22kC8Ht27C95hQG9yltmXCKvRNx3IR5utbTNA63dqgjTVlMWfoIQiAxOWU05lqbSmvKskSbfJ71coX3Hu890+mMQgi0yq642UzJIyXMZjPausa7lkTMNUAnVXb4FVkxVcpirWG1WrFarXjnnXeYH824ffsWZVlmpdI3KC2ZTqecXy7wKWFSZLWucc4xm00prCEGTZsCbQh4H7KS7D2t8xgbqJsagaUwJhPVGBApq4rL5RKZIAZPaFuUMGilEcJhtKAwCudaWu8QYo6UOex3tV4TfEAKRfCOer1ifjxDKknTNkwmEwAuzi+IMTKbHaGFQSbBum5oW8fqas0EhUUSfcBaibGWSMIkyeuf/3ouzi+4/+4DUtcvvfPQkdLj6Qnalp2br0cKKIuCUBa0RuN8ZMgzczjzbuh6NjESpCQPklIhtrmn24Vc66N9X+xroB4SUPf7+xD51Hslj9iGEG/DiZ8vPuh33YgPCAKkfLYO8v/6J9/ON/5r41czYsTTML7vRowY8TzxVFIqhPjTwC8B7ggh3gB+D9mRrQD+q25A+X0ppd+aUvoHQog/C/woOfTjX09ZvnkyUq61CWxJ5DVDIQbKCtApoXkb6NXSnYOSt+sR464CmnNPVX+d3W9JiO3OfmIvzy514YUxZjMlwb4aC3FAaEMIqA0Z6BXXuIm+PZiDF4bn7xXZTCY3DLwnCZuw567MjEidY6zPJjvBUxiYzgzHJyW2THjnaWtHWc6oqoLj4zmQidtEWHSnWDrnUEpx0oXlnp2dMa0qJlVJvc7KgzETmrahaWrKaSajTdOZ8KxWTCZTjMn1RLXWVFXF5z//eRaLS9566w1OT+5ijGG9XtHUa5xrmc2nhCRYrZYIJFrrHGZMIkWPNQVIxfJygSks05MJQiq8D8xnc1SnBF5dXZFI3H35hBACIQSMMVijmU8mnJyccHp6CjgkEZUCPmRn46ZpKKqKyeyEo5PbEAOP7r9DVRhKO6UqFFoJjLU5J7SumVUTQsg5pY8ePmK5XHH80l2MtUwmE3zraFqHFBLnHK13mLJAaUOhZ0hVYYsZ/uJBDn0GlJ2giwmX5xcgF7gIIQZ8cDx8+JBmvSB4P5jA2EIKuYn2iTFu+h2AUuoa0Tw0QbKv5vdQXc1YiDvEd/dZ2F2RJ2iys/KLho/kXTfiq4eA3/DP/nX+ufkPY4R93q0ZMeJjifF9N2LEiBcNz+K++2sPLP7jT9j+9wK/9702JJMrMvkkD3TZU0v6wFz6PNEtq+uOsd2Kzn23d6Ttj5p2DraXb3poO9gJ991ZxtZUaRt0vD3G9tpizojdOeiwXM0gUDn157sefrnZj62y3N+L1F1rvy7G/icTVaUhRY93LVpLSBIvErIzBtLaEELCe0cIOhsZCZEVVKmQm+8iEVMghKygIkDrrIgqKUndObOSmjakJofqqo3ZkNaKWqmu/E429wkuEyspEsYYXEz41RqtLUqqToneqmtKSqRSKK2ROucueu9JVuaJAQAhN/dok28putJBXdcQUuRKPSnShnYzUdA6hzKmI17bCRDZTTCEEBDSU4iia3/YTjoEj+/Cn+s6hx/Pjuakzm03pUiIHuElKlpkIpd7cTkEtyeHdV1jUCRpSLIFqYhC4YPHe0cMgdgr54O+sl/mZXfZ7ueh+dBmn53l23XDcPeU9hTS/c13nhmxOXrft27O6x70/Y8QH9W7bsRXhyTg50++xM8tRkI6YsT7xfi+GzHiOUMI0rf/bB59q0W9gM6OzwMfhPvuB4fNGDUS+3BaqbqB8DCPM+X4v00obiRtSl5sDrHdpVNSZadppgGJ7E8s+p1iHjSDymGw8aaB83CYnTYnTN1ytQkt7o8XCWGPGMSOMGS2xOYCUq5Lek1l2rpA7apZgzYmEknETE6jJMRAEoGilJyfP+Li4jGvvPIKUkisyUqZc56mdjkPNQTWbYuLmlIbSltS2YLF1QIE3Do9oVmvuLx4TOMdSoFRMC0Mqiyog8f7/F3MZjOstSyXS4wxKKUxWkF0rJcXlFrw2ZdeovGB4BqcD0gEk9JiyoJ17agXNbOZxHS1RmOMNMGRQlaAy6rM5K1piDLiBbhaU5aW6axifnyLlBLNakVdrzvjJU1Inqa+opzMMGWBiIHoW9rVJccnR5RlyeVigQ+e0igeXl7ivacsS2ofWbs1qnZYaynKyaaWadu2pBhRyTOdlEymE959/Ahi5POf+zzrNocZX11ddLnLoLRFSMWbX/lpYsiGX0U34H74+BGmCZRtYnJkMKVmOj9mtVrgWkdlK2RKrJtI9C0p7KqlO/nJG8K6O88xfA42Rls7G8hNbnavcArZ1wHuCb/YmYjpw3DTkChDrjMsbjJMioPd0/4RR4wYMWLEiBEjPhEQ2vAz/tA/4P/38hcohHnezXkh8IKQ0t3cSoC+rEoMgd6VMwt1cUPcBJnwRa6HCaaYQMSu5EemoFLITVjwZrtDKiS7pTUOueTuKrgJmeS1lUMlqheOdvJGB/msh9q0qyb1uYH7oZX7bcwEOcUcARxCAqGoZvONO/Bi3aCVprCWoiypqpLZbEaMkbb1JCIigTGGqqqYT2corXC+5fLyEpECQoBWCqnyfWtdQwqQjEGFgHcOKQTWGEJRYLQmxUhhDUokFpfnlEXBbDrFXVziu/a7EHBtw9XaUTdZZTRWIY2i9S1KaSazGXGZCHViVbcoKSmMIXifzU+mc7SWhBBxLiCA0iqM1lhjUEphtGF+MmM+n1NVFdOyRJKQ4TZKK4TIZN27yPn5ObIzWto4HwPHJycUZYmxJk9guEQKkWa94tH9dyiqCcaWXJ1dsl7WBP8jCKmR2nDnlZdICNrGc3F2kXMsE0ipEFJiDMQk0cqSYlZMpa0JSSDMmvVqxWq1xLm2U0w9B0vC3DynchBbdXtXLQ2EnWdgGyHQ972NRdK+P9mOEpsOPBs7EIf2GzEio3z9iu98/Sf5ZnsGzJ647f2w5Nv/4r/FnR+QwJc/kvaNGDFixIgRzwQpKKQfCekALwQp3dCufiBMQnRhrNvwW4ibkN3Yi5/bYwwNU3p1aC8qMeWDHiR9w/03atAN6w9ew94A+lCpl4NmMQfG3QcJKtuQ4aFBzUGCnbKKFUIO4ZVaU05mm5qgFxcXGANFOcEWlqoqqaqKGCNK5XxQyOG2trBU0wqpBOv1mrPHjyiMprQaIRVCJgSR1jmcCxRSEkMgOI9UEqU1qSiyu27w2RVXGKL3qKpiMplwcbXY3AgfIuu2ZblqaVuHa2tab1Fed0plxUl1i7ppENLRNLmeaVUU+BARAsqyJKWI9w7vs2OuKjVaKYzSKCmx1nJycsx0kh2Jj46OKbSm1JKmrWnbGqMXBNewWCw4ms83pLQvpXJ0fERZVaSUaJ3r1OlI2zTcf/sdZkfHlNM5q6slPi54/PCSYjKlms6499nXSYDzLavFguADRVkgpUIqjTaSmARaF7gQcW2LbluSUMimYV2vWa9XON8SvCN4d6Nf7U3k7mmk79BkyU4ZmbyQfsIkiZx9vRtBMHiGxDa6ID+/YtOXDz1bIykdsY+f9fLb/KHP/G2eRkgB3gmKb/5Djwn/8Cc+/IaNGDFixIeApBPaPFv6bpMcj0ODGMuTjviY4oUgpbBL2oAc4rdJrYw5ZxKRzVxSRIiUXVRFDvpL+zlqPT/rnGaFFIQB2ezPOcRmgDwsiTHIYez3PURAh0R3uN/w+obrNxe5t34/dHJDZAExqBf5pAG7RNLUDZdXLbdu3yaJxGJxycnJCZOqpGmyQVHrakgzSJGHD+5TllWnHBY5TLauefDwIQ8fPeJ4NkMIwXQ6ZT6dMJ9WhBDwvmW9vmB+dISShtZ5pFL5ymIipMB6uaJpa9brJV/7ua9hUpXMpjPmsznz+Zy6dSxXKx48fEzdNCxWa+rGAZLT0xO0NQgSy8WCGCKucTmPMsJquaJVihQTU6vQWnJ1taBtG9brNccnMwpr8KElhJYYPRM7ozCaEFouLs9ZLZecPzyjtJqTecl6vSLGyOuvfxbvGi7PH+C9J8bI7du3KYqCsixZLBZcXl0hhNiE72ohmE1nfPM3fzOruqFuPXfvvUJC4HzEhYRzkR/8wR9Ga4VVBpGy4p9EYDY/4uT0mHfefUTjPZPZEVprlLaYaorQFlVMWC0uadZrfNtmhZjrJkf72FfYh310ONHRE89+2X5/fCKE2J8LQkiJSLvhuDHGTYj6SEhHjBgxYsSIPUj4bb/0r/DLpz+KEZOnbv5rv/TPs/qdL3Pvyz/O6EI14uOIF4aUwi6RE5vP0Hu1pD5/NEakyIR0Exa7dyyRdg58Qw7dwVbQKz/vRRndxyHie30Avqsk9YT0WihyfxO4HlZ5+AoS3gea1mEqAyIRUsrEICW0EEgpqYoi57tuyHhnQtMZEnmlNo61zvsuNxakFDmMNUboVEelDFJqNJnUxxgzmRKduZFSGKOROTEW71wuvdK22bSoN0HSGmUMqXZICWVZoAuDVJK6KDBK453vwkdlR3S27RJC0rYtIcTOXTYSgse1+d6XRYEgOyK3bU3wAS8deqIIQeBcSwg+h2RL0f1IpDGberOiu38JiL1yL7ILb2odSQq0NagQkRG0tcQkCAS0EogEddtC1NhSo5RCKYkyEqnExmBZdCZM2zIuQG8kFQMxxEHfuN43xYAg7pPQ4XaHwsFvOt5w2dAIetv3dj2Otind1yMHnvR5xIivBn/4/DX+9Fd+HseLsTbpxxXq7l0uv+Nrufva4+fdlBEjnhu+pXiTn2GfTkgB3l3Nmf3AF0dCOuJjixeGlO4PmjcZmpGNUhjoQ3NjZ5YCfWnD1Kk7B1VQISD2DqXXwxCvtSUfYJckHyrbcuDzNcV3b5sY416Zmy0hOBSWu21D/hF76683PofsNnXLcrVmaixGCyqjkdETmhojYFKVvPTSPVL0xBCYVlOssYiU8r2Xkslk0hGgiHOOFEN2le1ql/o2E8ejoyNaF/A+UhYlIQTquqYoCqy1xBiZqynW3qG0Bd45Hj16RN00hBhBKRJQVRUohSoK1usGISTT2STXJy1KZuUM5wLtuialhFKaoizRSlEUBVrn8NH1es1kMuH09JTl6pzVak2TPKentzk5vcODhxe0bYv3a7QyGF3wyr1XKK1GipaysggB6/oql1pJiePjY6wxNE2D954QArYsSOQ6rGWZQ6Dvv/MOTetwriEqgalKklDEBEEmbDlBG4up1xijmFYVRWnRRmGnBVJpWrdGaYkxmrpZE0KeYKAJoDS69bRNQ0whTxQImXOr9yY1Ukq53z9BIe373aHlw58bc0B7p+De1TjtWYjFgevx4HzxvSa7jhjxHvBHv/t/zGf+gy/gx8mOjy3W3/Y1/Jd/4A8yk+XzbsqIESNGjPgI8GKQ0kRWQFP3AYjkUh6JHLy7Gez2g2Ygq4z5ECL1YYfdcpFIGwveTpHsJNdtbiekzmxol58OSGN/ss4kKA0G+XQ5ckIKSNu2pHySbVvSlkwKITYqbh6a9+1I2/MiSOk6QRXEXMZkY3o02GWv+VEmkkzUdUOyiqrQtC7Q+kTbOqKoKS8uKKzFdmVfcshmygqoAO88WilKY0Bn59u2rpFSk4Sg9p7gHZdXa4wts4usifgQaNoGXWcDoKIsidHTrGuSz2r37Tt3cn1PbQkx0jQNb731FpOjI+bzOVIZvPNcLRaQAsHVXC5qYhIINEJEpOjckbXEFAVNs4DoqaYzvA/cv/8AQcAazd2X72GMJYQc+q2VZFJN0UqhpWKxuMBZxbRQdDMhPKiXVEXB6dEJRGgaR4jgY8LFhFU6q6hakVrP6tEZqfHgEzHkWqIhBWw1QStLNS0RSmcSWRi0EBiVS+QIYL1aI6VBK4GrPb7xEBxKFxhTUhydgjI4JOJcEryjdS0p+m1/2AinfXhBl5+d4mZ5StvN8kTNIKw2pZ1nrF8foQvB7bqYzH1/E9fQFxhOnXTamW71W+Tnd+OGhOgniQYW2WPZuxEfKEZC+rGH3KsB3uM/ePQN/OdvfSuiVgfXjxjxacLbfsF3/Ml/m7s/GBlN3T4euPx1387jX7Xi/3Lyx4HR6KjHi0FKB2Gp0I0lRD+k3ZZH2c1tk2Sa1hFSen7WkUexDXfdhnj2A+Hhufp/9AZOuWLrirtd3pHaYYmYbrVIByxmUkL0ZWpi6gjsvuLU1/BkE6Y80IgPhlr215SbNgwz7o/bqVFCQJdHG6NAComL4GPAh4R0ntVqhRQSLXV2fRUyK7ndPUkhgJQoIZBa5xqkPiKkJMREGwKubWmXV8zmikrZrNSmrK62rgUB1WSCayPBRxwOIQTHJ8ckJFHk2qbeB87Pz7FVRVmUaGXwLtA0DVpGUmhYrj0IhTUCLSMQMokClNK0MUAMFEXJ0i1YLBZURUFpNUdHp10OrEcKkFJS2DKTQiVpmhUpagpdIVLOW14tL1BHx5R3ClZNgw8BobIBkQ8JKxRSa6TUtOuWZrEkeZ8JV5KkmOuvSiXR1mDLWa4ClEBqgyKhUybISPCtQwhJUgHfeoLzEALKCIy2TKZT0JZV6/MEgg/46Egxbp6BXk3v+4HoiGlKbDpZ/0z1XXifmKZBf0uDz/3T0Ls450mewaROT0j78AWx96ztp1MPifSBPj9ixIhPJ9Sd27THNw9Pvvf+N/Pmj740Fo0aMQJ4EDVf/90PR1O3jxEe/mzBT/zi7+YmQupS4CzWNP4FoWkfEV6Yq70+Fu2GvQcIad5+UEaGTExD2jp5ZrUybUbCQuzmlfaD9jTcZxCqux/a673vci4HLez2OeQguh/2mNnjHtE8mAuYj3XQYVdsifdGLR2EI0uh8CFxdrkmJs1sNmc2m6KlRMuA1TaTIaVIwRNck11shWAym9K2jsvLC05OT7DaooUkeM9iscAWBqU10+mUplmxXF4BEaUkp7fvUlYVxmaXXWMtWmtWqxWr1YrZbIZWmqOjo02eZllazi+vePDojNu3b2Ot5datWwgEF+fnnBzNibMpiMjVxSWPHl4gVAFS0ugaLbOS7l0maMvlktsnp9kVOCWqW0e8dOcUo7PbrnNuE3ZcVdUmP7QoS8rCEpxDawFaoqRCpkTpK0IM3H/0DsaWaGM5mh/jXGBxWWNs1X1XgboJ1E0kigRSUlYThJIIKamjIkRBDCB1r6x7rDEcVRW2NEgtuZWgrh2rZUO9XlCv65y7Gj3IFqUBlVXPEDzetYPZjNznt7nYXcRBP+nBtjZvGvSrm0J22TvOPvqJlBy12xPTPXfpFDfJ3Yeejb5TxxTprHk3z96Tzj1ixIhPLoSxhD9T8fs+/4eZSPu8mzNixIgRHzn+8mrOb/8b/yqiVp+qybcXgpRulZltqO2QkO5sOxgw94PXQ+VXsrKTj9UP1Icxr/3HZzEO2jlvf4QDeaM37bO9SnbamzbXuG1aSuLm/VOvg/VX0W0jemVKEGJiufYbR+IYA6EjujIEJDCZVAQv8a5FKoVUit6hWGmNtZbCWlzTDs6eiDGQUsJai7WSpl5n9VdKlNJorVkulwCoLs8zxkhd1xitKY3GOQckpATXZqLYNA0xRsqyxBQFpiio183m3iitsUWJc1l1jiEiVK7nKZUCBCFEQsihw8E1aJnLv2gliSmxXruN4VImpNkxF3LpG9fUhNA5zkqVDYY6tdyFgOra4p3P50+gpEJJiW8DUkpsVVI3q0wEERByeLE0FqU12miEBCQYodFSbr6/3qBptVzx6NE5Tb0ihIjWZTehEjoDJkHbtsTgu9DY+MQwxdTnXPf96ym5nIcI6U3P4KHnrl+++zxfV/2Hyv+uhHqdHI8YkWzi9tec8XOP/8nzbsqIDxtS8HNuvcG3l2No7ohPL9LtlpfuXfCyvgLGvOpPG1axQF5pnjJk+8ThhSClpC6NcePkmYCwE0a4s/neYLl3Q4Wt02dIsSOA3U5d2G0OP+wWxcOD7qFSuqPwsFWHhm05RIz3jWESaROYu1GxiAzH5jsK6DVslbD+c5ec1/3dEa2QeHRRY62isJLlqkUpiTUlKbVIAffu3sFrxbpuMEVJWVWEGJFKMZlOmc/nWGO59Oe5NqeUXC0vsoutaLl965jj4xnvvvkGbdsQyWRWa839+/cxxnDv3j2Oj48BePvtt6nKgvLkhKurS9q2ZTIpWdUNbdtycXGBEILZbEY1mVKUFZcXZ3jfEANMqimz2TEP7p/hgyf5hJkYjDEU1m++y9VqRVMn2maJRKKF4uT4CK0Vbdsym82Yz+fd9pF6XRNmU6SUNG2LkmCtxEiJUJkwxiTovYlTSiwWVyhpsMZSFgXaaBZXl1hrmVYV9f2a0Hpiitn8KURO7x1jy4qynBCSJxKwtiB1hlC60CAEZ48vuX//Pl/5yleYTqcUtsDaeS5nFBytqwnOs1is8M6hpMClSFbX5c5s2oYYigExZJe/DhXJJymmQ+yG0N8cGSDEdmJpf9/9yRbRhQDsq7wjRmwwd/w3P+e7R9ObESNGfCrwT3/dP+HPfu1fYySkIz5NeDFIKTnSbyfAcBP1el2xuZZfKnP+nuhja2PaVYg6lWuYd7c5b5c11w+on1yHsT//YMmBQffBWqYk4t6hr5NSuVEHD9WdFMjOqybtLKXTzEJIhJgIUiCUQGlFYXK4rilLjBRoKWjWK4TUzI+OuXVyxKQqaJoml35xjnD7FilFVqsVk8mE2XRK3SxJKXF8dIRUkvV63dXHFJiiQghFjCk76AKr1YoQAkoptM5lXB49eoQQYK3F+6y6SimpqgohsgLYNJmoKgllYRBoGu9Z1yuWiytSBF0YXJvPraRCKklRWoyOaAXzoznBBXzbIm1BUZa8/vqtTS1R7z0kmE6npJTJrJQSkSLN5RJKhzGGcjqnKCzVZEq9WtI0KyZlSeMallcN5SwfWxBx3uPayHK1xHuP0gVKZqIulSYmWDc12kq0VUyOZvimYdW2RB/xruGNr7zFar3Eao0UWQVNKVDaimp+hC6nNC7R1Be41uO9o49S339m+t/DnOyb0Nckfa9kcHfz62qq2Pu8//c1pZXr24wYMWLEiBEjRoz45OPFIaVpP7Rwn4huVdQ02Kf/IwFyhyzC1qxoYyi7W790Y8RyPbR2e5x0TS3tjWR2WjqUUG8aUO8v786fiajIzLwLLd4fru8s6UMxe3MZkXNmY8iKYUzbeySEQkqFFBKjFUbJrLJZSVEUGJtJa9s0mVg5R/CeoBTe+0z2+4KUgNYqu/CGrAYCSCHzeX1WAGPMhkK5Tmi+fzEE1q2jKgukzA63QuTwW2ttVruVynVDQ+xqjiqk0LjoSQS8a0lJoIwm+ACb3OF8M3vFvCgneOlICaTSaGM5Pj5muVzinMv9QEqMMTk817XdV5EIriWofM+MsRhbYk3JOq3wIRJjxHtH065xzRqlJIKEDx7nWpx3BB9RGqRSKGWRneOuDwEjJUorTGHoSxuFEPEucHm5IIQWpQRCJAQR0YUXm64WrAsR77ORVIxp0xeE6N2pt/12E2mQttv1anzfh3vLor5f7ffcNNjrQOfdnOvQXE7qVdD9kHx2n6GBmNsdeeuUPWLEe8FZWPEDzTFm8bxbMmLEiBHvAxLiNHBqV8+0+T9sV3zv4lvB+Q+5YSNGfPh4IUhpIhGFp3fyJEEKu2qKAOLAY3dr3JI6d9uEEHIzOM6qYi6t0iurmUR1iujmvxvadKOasz9W3hnWb/ftVMCdHfutd/hln1MaiaG/UoEabJu5XwIZdoitQJCERJKQJHyEECC6hnV0+FYRQolWYNZXxGqCtQXFtNrcxZ9+4y1SjHzj130eJSXROR4/eEBhDSfHc0II3L//DsvVmhgjV5crqqrMtTyVJQbP4vICKQRSSY6Ojzqi12zI5mJxDkJiqwnL9RohBa+++hnUeoW7vKKazlFSsqpbmrYhti0qlvjgWTcNx0cz7t455fzRGa7N7rnr5SrnigqP89A0gq95+YT5tODs7DFKSLRU2bwIz7vvvoNrG1zjePWVl0kI7j9+TFVYtDSIGJAC9LRgNj+mqiaI5HD1iqt2xXQyQ4oZjx8/piwNd156FW0LBGCkoG1rVlcXKCHQ1lJVFUlIkAJdFChjkVJTlhpj1Sbn0tiSVeNZ1w49mUG7IrkFWoBRAmNyndfVekVhjvE+9xCtFNYamtDs5GcmtlECdKQzPzu7od/boPIMJSRRZqLb9/GbOOGTogl2FU7RRc0PQ4vzsxE7R2opxWY+R/TPPgmZ5FPzX0eM2MfvevOX8c6vPublx3//QKzJiBEjRrzYSCeO7/3OP8hLSvMsobv/0nf/Tr7uj3yZcP8rH37jRoz4kPFCkFLolJ2YNqVeBnoKPYuLMQ3EyK2CurtsG6C7NRLqwxcH6utgXN3/+eTQ3SeEK24asF21MSF6yjX37rn7m/bKsRgKRjsJgdfVq9QTWqVQOv/0V61kVkbLakKSAq01s+kEEQIxBJSSkBRaqU3b27alKApmsxmIc7zzSCWJMbBarphOCrQxKCE3qmpd15t6sb2DsOrMiHqn5Pw9C6RUKKVYLpebey9lDvdtmu39c50hUVHYXLYmJLTRgMSTa2sKUi5rIyXBtQgFQmliiMQQSClmtbhTWUNK2Y1XKbyUTIxBa0lRKJTWeRIjRLTK90qK7Bo8m02RKivwSkmkErSNx4eQ1eIYkBuLZpG1Qim7CZNM3FV3j6VS2LLk/PIxi8USkSKSROrqqBqlUCIRvKdd14jS4QJ41+Jc2xk19f027vfKjRyZBl10043Efn/ud9h7Dm7IId1HH8Uw3LaPVhiu2TyFAxLaPwPDdqTBcz9ixLNiGSz+zbdujlYZMWLEiBcZMvGS0s+cP69XAv/Oux9yo0Z8UFAv3eONX//1vPLfe/t5N+WFxItBSlNWA3eIY/f/4WA3K4pb190hrpWREHRK6RPy6XbCXJ+s/uybuuyv32nLpu174cBiNywxk+Y4XE3vvhv7C+7bJnbvTFZJt7Q9AlEIkpRYazFGY7RCiIgUAm0Vs9mM2XzO5XKBtZaT4xMqa4ldqC0pYYxBa70ps3J0dMTrr7+OlIq6bpASzs/PuLy8YDZ5icJaTKVZLZfUdc3V5RVKK6bTqnPapQuTFew7CwuRCfTjx4+JMTKbzTJhk5LFYkGMWW2u1zXrFKmqCqWy0U9VTtHakLxAEPBtRGmDVBpfR5RUCJFdeb0PCCEwxiCMoa5rXAg4F9DCoQSU8zlFYaiqghQSIQRS8GhtKEvbfReJ27dv0bY163qBVBKpZD6e88QEMfpMaGMkCUVWCcUmX1n2jsEik1090axWb3J2dobwHpXlcgqtKLRGkmidY1U71KTBBWibFW1T0zQNRnU5xenwJEgc9qG+r/aEdBBt3n81156DvZD0Jz0L+wZg++jvC+xpp2nYswfbj0rpiBGfOgghUKPOPWLEiE8gwudf5nt/x3/IPTV93k15IfFikFJgQ+XSvhURAyJ32IgopgQhZrOabn2IAxOhG5AAub/sAOHsCcVNZWAOD9Sv56IONshkWXR6bsfF87V3bEGwGeXHlLJ78CAhVoou9FiI3niXy+WKRe1ofCTEFu8Fp8dTysIwnViq2ZRqMiWKnAf6+NFjSquwWmO1JgDJaE5OjtFas1gsePz4Me+++y6nJ6dopfHeIYWgsJbj4zlaaZp6TTWpqKqSmBKxK1/SGye9++7bVNWE27fv8dJLL6GUIoSANZbbtytEp7QaY3AuELwDeiVVQ4rEEFmvL2hbRwiB+bRiOp2xeHdJ2zRcXay5mGlCLFECXNvi6pbPfuZlppMSKTVK5RqkWipsTEhVoqVAK4Etqy5ftiv1oqANbc6fdQ1NGwCBrQyohC0NMXhcDPgQsEVJNZnQNCtiEkhdYuwUbSdoY9BGUxQVWuX+EXygqR2LizWLy0va1RKTAqY7tpESKRIxOIrqiHJyzOT0lNWqxq2vSLHtFNu46V3pQP/t1enBgusPgtiGscuuTE0m9OH6toP+fj0HW2wOH0I8eKp+/wTXn5lBqaQRI0Z8+vDgf/sL+dpf9xP8xlvfC8yurf/ra8lv++L/nKsHs2v/do8YMWLEiI83XhBSuktIgU166VDNfJZovo3qEtlTQZ8+0D2kwu4rsDeppDv7HFi/f9zY5dZt1eDdUOWdc1zLYh38LbZKauMcdet3QiSlFLkkTJFrZUolKYwlxoRrWypboTuzHkEOj+4dc/u6o+fn58ymU5SUmRyn7XmF3G2HlIoY5SZ8t1fH+vI7/bGbpkEbgy3KTe5pDnHNBkhK9jXqEiSJGMyc95MPggQxkkIkhEDrPM4HikoTXMB5n8NuhcTHmOupihxOK6WgQiMFKCXQ2uRwXFJ3fNDaIHPk8eB7zsZPWhtiDJ3Kn1Am12VN5GuNQqG0QWuzuTatNYhAioEQA651LJcrmqbBO4dRASU0hTEYrbNqrCTaGlQ5ye2RDdE3pBiyudHQxOhQF98Qvf5esvs8dbG9abBo2G83y/ZLHF0jpPs9k53Q+n30E03D52LgvT1ixIhPIa6+Bv7c1x0mpADv+GOWP3U8EtIRI0aM+ATiBSGlA0LaDZoH/PTagBmukzzY5jDmfQRPZbEpEQdbHVJh91WjQ/VLr+1D726adpbtD+z7VvZtuZ5/lwaktm9k90GKrHCp7d9rF2l8RNkiK4lVQayvCMFjJyUhReq2YVKUiATBRypbUBhNvV4TvMO5hqurK4wxxBgpioJbt27h6obkA9NpRfQtq6srHjx4l6qqmE0mnJ+dsVgsKbq6p6enx5v79M3f/M00jWOxWPH48WMA7t27h7HZiVdKjRBZ2VbKUCrblYhpuLg8p7AWbQtOT3NZlxACF+ePuf/u20QpsEpxPDtGmQKU5uTWbXzraFYN68bhvMcHx6SsmFQVhbEYpZmWM4zVGKMwtkArRWksMTRA4NbJPRCJJALTudp8P0orjNU0qyuC952ia1C6INUtkYTSNjvy1ksmxTHQkfPkSCkQSDRty8XVgvVqTdvUVBOJsQWTyYxqMkcZi6pKopnhleFquWJxtSDFmhQbUvKQhgZGB1T8nf40JH7d7710aLow4JtC3g8rpP1+w2e1HzZ2ua43HHN4rGzQlA5dxogRI0aMGDFixIhPMF4QUpoO/HX48xCbgfEHMI69yW13uG7/75uWZQFqf7utWrs5F51b6kYpHeSj7h2/E7Q6TrqXm5my0uWDzwSsMykySlBqtckTjTHSNA2qD1GV/def0FqilcEahWu7WqGdqlkUBakzMrq4uEAIwfHxcUfWPW3bUlUTqrJCakNKkcvLS4BNWRjICudkMkEpxWQyoShLTF9H1RhmsxnL1ZrVao2UWVksyxISmxqjKUWMMUiV1UznHCFkI6HVaoWPDe72Ed452rYlBIOSGmvt4KdAy9wuayzVpKRu1kQVqUxJXde07Zp6tcIUhsm0wFqNUhqjDYmI9x4pJEJphBSEGFnXdVajE7gQMuGT+R7I7nx9VzFKo6Tc5EwLQEjZqZaCum2RIWZllwKhcp6rD57gHDFm8ybxtL6/I9tf78u9kn2o3w+dr3f67aFnJG8wWCfYrb807Pc37H+ozSNGjBgxYsSIHfzF5YTf/l//ej7399rn3ZQRIz4wvCCkFPoczBx2m/pFhyF2fg1yMbdLny1g90ArnqAQ5fWbDXcbcbCRg2MNHXaH6tTO8fby//ZJrOh2HkT59uVnkgDvA61z+BCpJSgis+MqmxEZQ1O3eOcRPmKMpSq2RMka3eVXSt558IimdVRVRVEUHB0dUS8X1Os1Z2dnnJwcc/v2bdbtihACTdNw6/QW89mMCFxeXvLTP32f+XxOURR474kx5/z2x5zNZmhjUdp2pE1y+/ZtYnyYnWi7cNfJZEK9XlM3jrqukVJSliVG6+ycu1oRggYMV4sFqoa6uUNo8/bzWYmwmqqqKIuSoiioygqRwDceYyyTyZTzy3OC0hxPBavVmsXVGd45ZvMpSt9FqxKjFWVZ0bqa9brGSolQEqKgdY62aTiaHQGC9WoNMuf+KqVQSnZKfgJBF56rt91IADIT0hgTTV0ThcSkhJEV1nak1DmcawmdodKwQ2Wl8lD/HfSjPVOhHFods9FVZ8TVk9XtpM/NT1Laee5SF7K7R2Zv3HsQHr+zQ9fBR3I64j2gSY42qKdvOGLEiBEfc/yp+9/ON/7Wv/PEf59HfDwRUqRNn85/y14gUpohZFaNYj9YT725URr8wHDEmgSktM0yudko5TBV3UnJS+lavsqQkKbYEYhhGRhx0zF3TWDoKkZut5DXzz/cs1sh+xIZka2xUXYrynmeCFKSJCFAKpQ16MpiK8vRyZxJVaAQmI4g3b13B+88F+fnTKYWbQ26MATf0NQL7ty9jRSS1XqNcw0P7r/D0dGMydGEu/oeAsm69RTlDO8cj84esVzVVEXBa599DSUkSkJVlkyqCYtFTXArlosVy8USpRRN01IUJbYsefnle8QY+cpX/gkhRKzRLBZX1HXN2dkZs/mE6azixB3hvad1DaawuVSL0iwbz8XSU5lMdIUw2FJhjKINAb9c0/jI6bGiKKYYU5FSZLVac7W8wIea5GpilFwtH1JWBWX5EkSHlILQBM5WDxFCMD8+oipL5pM56/UFrqlZr9bECCnAhfMIqUFXFLakqApShOgjUufM2BTh/LLh8eMrHj+4j2vWkDztukVGj0qBYnZCUVTY2SmqnCK15sGbb3J5cUauySt2Y9zZhnvvKJkxbpI7+8qfcRBnm3uPQHTL+hD4ISG91ru7rrw7gZO2z6kAIeTuP5YChMrKcCR1j0x3P/pN0iaN/MZc1BEjDuFhWPLLfu/v4t7fXUB68LybM2LEiBEjRrxnrGLLL/3ir+Xd+8eHqMUnHi8YKU1dWZTt4HSDa2ZFe4PlnXzNp49oD+XFDUtTHCx7sTmhZChS7eekHlJbxc5f2523hHSoqu40qttyn+DubpdSXxYmoTpzI63VlqggSDGRYsxho134a38Y53O90uyKmw16XBcC2zpHiCGH/GqVlekkUUoTQuzKrnicUrn2p/c45xGdg24MEe/zNn39yuViSQix41XHALRtk02OurDhXl2MIRBjbpcQEELILrGIbtuINoKU1MYESSqFUAnXeGJM6JgzfYVUILJhkwuB1ju0E7i2JWmJcwqji2z0JCUpRkJXDxQhiCmCFGhrSOtEiAHvGwQKITTBe4QSaC1zWzo325gSqlO6YxKs1mvW6zW+rUnRQwqkEEhBEUOuy0qvjAsJQuLbFtc2Xehu31efHE6+7buDPpz2Pu/1pV3zoWG323+uBjnPA+fdnQNuunruwUmka2T6JhwK8x0x4hBcStz7uwvSD3zxeTdlxIgRI94X0i3HndtXyNHK61OLSMyE9JF93k15LnjBSOmHhzx23rrBSpnJz7PvvyW710IbP4Sx87NRa0hEAgKXoI4BFwMFnkIVWC05e/SQdlJxNJ/Rti1NXXN1dYW1llu3bm1Uy9VqiVGCSZHviRCCqqqAnM+5XC5JJLwPzGbHzGYzpCSTRVtwdDRnOqlYrK64uLjg4aPHnJzepqgmLFYLmqYhxsjR0RFSSh4+fMhkOsXHgO/qpJZluTn3bHaXpmmAxOXlJQ/uP+Lo6AhrFCkKXNNm8utbhIDZtOBs0WxqkiopkFITXEQgmM1mVFWFNZYQPK51rNc1hTUEC4/Oz7FaURTZ6CgoRXk0wTUtq9WKV159hel8jiizskxhEUuBkIkoAoWxFLakcZDQoCQhJZwLCBPQSoHSyJQI0XP/wQNWlxdoAi6sSaFBa4OWCa3Au5YQJXW8ohIlVSnRSqIEuV6sGLgQ3zAZclMu9KG80qGB1411ffv1XQ7s9VDzvYmcXpHtyfUNx9s956dwanDEiBEjRny6IeD/9O1/gV87fxcjPp2EZMSIp07HCCH+hBDivhDiRw6s+51CiCSEuNN9FkKI/1gI8ZNCiB8WQnzbszQiCzfbXLaDA9O9xcPte6J5aLA9XLfN38sD5D6fbt8ZdNie643YvwnXz/dEDMbmN5WZobMyPVRzsv+RXVkTIQQxgvMRKyWV1cynFZPSUna5lNZaQujImlLUdY1zriv7YnItUMRGpazrmtVqtQnllFIQu/tnjIHOSCkfx1OWBbJ3KBYglURpS904lqs186M5p7dOuXPnTg65lZJXXnmFO3fuMJ/PN+7GmRxlQa5tG5zLZkvee1arNefn51xdXeG9p24a6rYmpRzue3pyhBKJ4Bqcc6zrmsVige9UTiEE3nmWqyVN3WRFuKyYTGfMj4559dXPcOfuSyipCd5RNyuauqF1LT4Elus1i+WCFAKECDFRFAWT6ZSj+TFlOUFKg1QGqXRX3ibnnBprMDYvV9qgtEVISwzQLBeEtkZEz3Q63RhAFeWEYjKlnB6RpGK1XlOvV7i2Rquswl7rWnvq/lP7YrfP8Fj70QPDPrftwuLausNu1B3hzA3aUXU3pYx2zsPOsZ6l/R80Por33Yj3hs/9rLf4dT/7ByiEed5NGfEhQX/Na/zkH/h2/plfcu2xG/EhYXzXvXiwImDEpzOX8NOAt3/nL+KnfrtgNv5bdiOeRSn9LuAPAd89XCiEeA34ZcBXBov/OeAbup9fAPzR7vd7Qtojn/mEO78Obv/kQeyW1T4xzPZJyWwHDy9IaVv24unH2bV/eVKbh26nQyUrE1LZDeIz+QghYqRCasmsKqgKg9UKbbMpUAgBITMpbdsW09UhVUrnWp7dMZXSnULZUlXVRiHu1TRjDIlMSmP0CMGmzmiIAS0lQuUSK63zrOuGO3duIRBEHzg/PyfGyL1797JJkBBcXl5uyGN/O5qm6RRUSYzZTKltW7TORLt1LW3bIklYqzmeT1EyEXybXXqjw7k1pa3QSiOEwHlHWkUUAqUVRVlSTaZMZ3OmZYFvG1aLK5qwIviGtshkPpJYrVdEEpPZjKRybVRjLFoKlFB4l3AuIRVEcrit6O6FNhqlt0RVKZlJaYRmtULRoHRWpm1Rom2BrCYIM0FOjmgCrOuGplnjOlfknfJH74G8iT6M9kA/7b/jm56PzfJN3vMegd1XSgcn2g0D7sJ9OUxm80RLvLb8I8J38RG/70Y8Gb/5tb/Fr5mfAYcHa4tY824we/keIz5O8K+c8oV/+fdxT02fd1M+TfguxnfdxxIPw5LLtnzezRjxXiAE3/I//TG+5/P/NTAq4TfhqaQ0pfQ3hRCfO7Dq9wO/G/gLg2W/CvjulEez3yeEOBFCvJJSevu9NqxXK7s2PCkCcONK+36VlYN1F591n27w/aRyGR8WhBAgsxIc2shEWZKCQgmIHtcGqumEqiw4ms9p2xbfupzb2Yd+kk1pjo+PkUSkCMxmM7wPvPHGG1kNnEw2JDjGXJLFaEuMsnPfrbGzKWVRUDdrlNJ89rOvo5RGyax01us1F2cX3Lp1C2stDx8+pCgLyslkm7vatqSUlevekXcymfDSSy8znx+xWCyyA633uSyMFKTo0EohBMyn006lFKSOXDVNQ/ABrTXTasKkqljXa8qy4s5LL9M0DW+99TZGRFLwtPUaa8UmlLgoS+Ynxxt1OTpP4wP1ckmIDYhEZS105k4Ev/l+pFIYbXHBEwCFoGk9ddPi2oBAMakqTAItI6umJSCppEFGgUgSLVRXVkZsrLKGpPGm/nYoX3ozsSHljhI/DKHty8Ps1A/dJ6dcJ7Wio6Q7z0GWSPMasZv92hPSXVLM5shPCyP+sPC83ncj3j9+1l/5N/jG/0eD/JGfGIO/R4x4Rozvuo8nHoYl/8K/97u4/XcejRNxIz5xeF85pUKIXwW8mVL6ob3B72eAnx58fqNbdu3FJYT4LcBvAZgatWvY0g9I+9Gv6H+lfogLfBjZZ4MBMuwMsnfX7zgRZefSzcfUtb/bQ/SGMSI7afV2WgMB+NB7ZYeQb1TSrdfM8LZnMhEG+a0pO77Chtz5kOtqZlVTdmpbyHe0D6WMueyI1v25tyHRUnTGSCkgSEgByujsTutFVltFNlNSUlEVFSC7/M6evCTazqinN+vZKr/ZgKgPqe7NjGxR0Jv+aJ3b7FxLDIFcPyiSUiDFQFVaRJ8rnDwigVTZoTemzpQoeIxWhBho6lUOx42+O4YnxoCUNofbSgkkoncYbVCyUyhTIAZPkjET447MOZ/wMWZfZZmgU0y994iYAIVrW1zjcqhzijn3NQmyWW0kpIiLERUSIiSS8/iYCD4SvSMGl91zD2BYOih3w31SOcj73GzTr8n3WIi+zw132S9VtNdpDxFjwdZoulsgtqfeGCP1E0r5/2nrwbQX3vs88dW+74bvOnV6+uE29lMI88DA9/8dnpu2PuJDR0iRv7Yu+G8vv/F5N+UTjfFd9+LDpcTpP1wQfvQfPe+mjBjxgeM9k1IhxAT4P5DDO943Ukp/DPhjALcn9vowux8sD0hcn5u2DSPcrHoGVeVJA1yxs35LgHfp5+asXfhhb/gCYic5d9MU0f+dC18I5LasS0dSNyrw3v6HQ4uHxLRbH0VHiFpq34IQxKhyWZKkKIoCIeDx2UOO56dMqxlVlRlDXa9QWqO0IrqG4B2+rTeE8Oho3hFG0NoiiCR/hYwS0Ewns+zmS8xGPoms7knNdLI1LZIyG/QQPG+//TbOOV5//XWsNdngqJqgtCdJjXcN3rc8fPgQgOl0yuXFGcvlAmstzjdcXp2jhUAKSMkhJThXcXo0RQhFkJZ6HXDrxPT4GGMtUiR8CizXS8rK0rian/rSP+LurducHB3TNmuIHoiUZcl0MiEFR1OvuHp0zuuf/yZm82OWqyuiXxP9islsitKGFH3Ow103eEqEMlQaEJIkNOvVJUJIgkk0taNpPL5dE0IDIhJTdt+VKhPsunUo7RHRg1vgQ8AFR728oK0XhBg6ZbLvdWnvt9gQ077fQNqQvdSLmLL7LfpSMKnzg45bX2ghSEJe79hiL6dV9MR28ByJBKE/TP+kdH1i6Ectumer2ybEzoX72hPw0eODeN8N33XF66+9CJc1YsTHCuvU8lv/u9/0qXWk/Cjwgb/rXhvfdSNGjHhveD9K6dcBnwf6mbTPAj8ohPj5wJvAa4NtP9ste48YjKYH4+AdDEfd+3vfGEp7PaRxeL6d7TcS0lARun6ojTh5YPPheXIIIzdu9KymNMOmbffNZUbazsW2qiaQMm3pc/NSSiyXS5p1S1EUaCWxVrJYLNC65mQ+Q0uJlgJjcgjsdDrdhFi2TUsKHlJiMiuYz+c8eHA/l0ARguL4BGs1b731GFtYysLm0NkQKcsC7/zGzCjGSNu2KG0w1mONwRpDWVUsF1csl5E7t24TY8SHgHeReu2YTOYYDSRJX5YnREcIiRAcKUYikjbm8jZKa2bTEmMt9Wqd62B2X4NScnN9bdtycnKMFBD91lxJK0lVTaisoSgLpJbY0uSJhaBQWoMQtM4jtWEytfhUElHEmBBSoK2kVHOkUpR2ik9XCOcRMZC8o23WTEuFtQW2qFB2grZznLREIYnk8jGXVxc45zLxF12wbMrq87Y/HA633e072xzoPnx7R4IntzvF3E87oRTZTaTE2Cvn16ZS9uIYuuYNypVun5Nh2HDfPhBdSLEUiSSuP/LPCR/B+27EiBFPxUhxPmyM77oRI0Y8V7xnUppS+iJwr/8shPjHwD+dUnoohPiLwL8hhPgechL8xfvNJ+3O9cz7fLU5aGmgAvUhjDdtMzyXANJQHep01usD6t3SG7vnfHYcCmlMQEBkhUkmjLGd3NqfN5+rbVva6EgpmwNpbfG+wTuPPDpGaNmVGhFIKbDWblxc23XdldJRGGMpi4Kry0yUptNpDq9Virpek2IgeEdTr3O90hQ7997t9XrvCcGTYq4xKpWm0pbgWpp6zaSqCCFweXlJCJG29SipkTJnZ2ZimoiRTRt9cIQocDHr2EopisJgrKZd529LdnMZEkFRVVnBDJ7JZIKWguANwefwWqM0xhiKyQRlNNlZWCEVKKOIJGJMhABKa4y1qDQhxGzU1DsRG2NRymCLCWq5zjcgemJweO+QaoK1BdqUGDvBTqYEb4hJkoSkdW6TT5vDrTMhvSm6dX9SZr/f9X8N80E3IeebvFNBDOFaHmsffr4zydKfo48b2JyXrYJ6sNd2RxK7sQovSNQu8NG870a8PzTJ8WXnUPUL1GFGjPiYYnzXvfh4GJb8qDuG52cEOOJ9QJYl8vSESi2fuN0qtjwInmet5f5JxFNJqRDiTwO/BLgjhHgD+D0ppT9+w+b/BfDPAz8JrIDf8KwNeZIj7jPsvfnrgzBH2cmpe9q2eYedfKbNADulzSB+99g3t3c/l3T7c0hgzQtCSrRJMD86QgnB1eWa2axgOi2YVCUxRRrXcHJ8TFVOWS6XGGOYz+coXSCF4vLqCqMkZaG7Wp+5Dd57nHOcHB8xmVTcfukOF2fnPHhwn7puMFpz9/YdrNbEEPi2n/NPEUIu4TKtSoINXF1dobShKCtms65eatMwmUyoCsvDx4+JKXHr9h1SjBilmJQVIXjadY0g4X1LXa87kyOFiEAEJTVVNeXevZd5+OAxbRt45ZVXWK0WnF88YrVYUFiDNZbCWgprqNcrotbM7txBkUNJF1cLpARJJMWcq+rbBq0kjTE0MaGMpmnXFFoxKSymKFFaUpSaCMQkKMqKmCQekcORA4SkcCHRNAsWizWrVc3i4jGxXjGrDGV3LGnmoCuiKDDlFC0NmAl1U1NcXeBrQUwQU0SKrBYP5YN9MnrTRM0mn3MYQjtIdd70ue5z7P83DLsV14+5VUp7BZadEPiNmdKhCR8ScnDYuHNlHx0+qvfdiK8ev+/Rt/K3/pVv4/Nv/ngfJT5ixIhnxPiu+/jh5/2l38HP+AOP4cs/8bybMuI94J3f9G38n3/7d/GLygfAzQ7jv+Ot7+Cv/vDPRC7el93PJwLP4r77a5+y/nODvxPwr7+fhjyr0nm4hMSNkbzv+VjvZyg83GNDKnslqU/aO7TN3u/99cM27oY6isF5E75TErUusvFQV5NUa43zDiFgMplgi6KrTarRWqGUQkmFEAqjDYKIc56UsoNsbzgUQqCu1wgBzvkcmiokk6rMJkrOYbVGACH4zsF1284QAkobrLVdjmvOM00psVqtOvOjxMXFOdEHUkxopUgxslqtsNZyeusEaw2QkEpk4kjCWptrpyKJMZcQTSmhtGYymW3K3pTFBCmAlHLIccpqrS1KSmtJKRBCJKZsQCRSQkgQQmNsgfcOF1xeJiVCKvrpByElKURCiCTnuhzMfmpC4n0EBEqAdx7XtETvSNFvczcTuBARSSCkQoiskiYhOrVVZ9fcrk9lk6Kb++qOMjqc8OlzmHszIbZEtM/b3oQH931vmCr6xNmaLZnttx1mXveQdBOB29kbNjdhuPg50NKP6n034qvHmZ+QfvRLRNc+76aMGPGxw/iu+/jBXCjCj//k827GiPeIdg7/k+mKJxFSgLN2grz89BJSeJ/uux8WnkZKXxQ3zn0cVj575nBz3ushdbgPRR0imw2JHaI33L51nuWq5uioREiFD20Xfmu4ujinKAo+89pnSR5iyHVFrdVIKYkpm9vMj45o1iuuLs6J0ZHIpV961ezdd99Fa0WQgsIYptMpUt7FNQ0X54+x+i6TsuDB/ftIpZjNZjiXy8/0JV6qqsI5h7UWrXM91Hfv3wcEIUYePXpEVU2YTqZYa2nblnfeeYfbd2/xmdde4erqKqu8V4rWexKR+dExRVHQ1A7XRlwbWK8XFGXF3XsvY3AYrTg9uc1qsWB5dYlvHVEFlsslx7M5JycnLK7OCM4TfIvoaJQuDLYoOD455d2H///23j3Wliyv7/v81lr12I/zuI++3T3dDTPg8cAwsXkpHhyi2A7hJYKDZCVDQBCbyHISKU6ClXiCFCn/xUqCgy38Sogt2RNwwOAgEoMMZiwbWzCMDTPjGWZ6zAz0u/v2vfec/axar/yxqvaufR79os89p+9dn9a+55yq2rXWrr1q9frV7/f7/l6ksQ03b96gKiuKskxfcQAQgk/fQ2uPQDSFGSFoBEOzTt9HUVXYpmW1WBBcizhL7Ix45yN+1SBmzNhUtFHhIkQXENFUVY3WGu+TQjEhJuelegu5l9v4+M5wTOrKSVQs0pd3ke7BgaizQtlPbBDpvLe7B208pp0R3B/r6O+Nfkf3+yaUN76lB02ZTCaTyWQymXceV8IoTWvV5PmKvTSoSmIqW/kViEE2i9Y+RDDGMMhZi5uwU9XHDg4b2Vm9Dxe9Q6PytOe1L69xnk0sg587NSAjxJhKpZxuv39Dl8sXB5l3Gw/rbh/6WqH94n2zLyRv6fHxPUZVyZM3b1Dqgugc3jmCMRDovJ4BJF0zHyJapfIuAhRFyWS6x2q1IHiXPHRlQVWVPPrIjc6IDan8i9ZE54jeo7Xizt3b3Lt3h0cffxQlgrMNWqA0hkKEaC2L2TGr5RzvPGo8olkvOb53RF3XiFKURqHFE31Ds1ogMfDE449T1SVGaUIMyRNrA6I0ShvqqiJ4z73bt4kRqqpkPB6jtUFiYNms0Uqoqyk+BFQXRqy1oipKmqbl3r0jjFYYU6L6PhvNwf5eMj5Nyc1HHgcCZZFCZr33mKJESfLQoiIRj0IRo8J7sDai2oBREEJksVjhg0dpoVmvUaGhKAJlNaKeHFAdPoYXzfFiSSimKZ80WGazGXfvvkLrGkJMeZ7J7ds7LvvfVXcPyM7DjZ2HHElRaDBue397GlN6oCO9rV3qdxV8d4Zo3NiVpx/ObBWsZVMWKB2jutI5adyn4PcwDPuN275lMpkHFBF++3/6IO/9N3+HA5WVdTOZzIODeeJdPP2/3uRPvO+fXnZX3jFcCaM0LT1TiGNCNt6qfmG8MU83Ai/9sYqIZ2iQntBk2aU/zWusd0/u280DjRsjdXO6wf7UtbRk73PRN6G8w/y/3e6cNkhPhOoOj95+xpjKypCMHusbCkWnngvBh86bF3HW4VzyymmtSWG/ni7DMNXNRCjLGmttd0VDqhVaGA4O9hER7t69m2qJxq6EiKT2ZrMZ1lqe+tInEaBZr1KMZky5giG4lBNqW0KIBOewbRI1KoxOIcVKUEQILpVoQdifTkD1QaC9MaXQOoUAG62xPmCbNVLWmEJTl1Vn2ISuHqokYaWQjCStU/iyMQbvHetmzbiuulqrGlMUnTe5RhcFKMO4rtEKiBbvWmwXIi2qy7LswqBTmRZFDOB9xPl+bHha61I+paTQYYNHGcGUFUU1YjyesrKexbJBdCBKxLaOddOwXC2IwW1GyslQ7uHYPMmOMNfruFV15x3d5jSfNe76cdoZvmecs4sG3gnMPRVS3D+I6SOY5Q10MJPJPFB83Td+lp94zz8CijP33/VLnvdCDGcJCGYymczVJO5P+JkP/nW+qhy95nE2el7wK47b+j717OpyJYxS2BqCQ29KXz4Eer9oL+yy60rsM9cupl+73qaTa+ZNb86wBpSS5Pl9jXOeG7I8DHfs2OZqJkMz9UURQ8T7wM0bN6gKxe07L3J4MAWZMJ6km+GFF15I9UK15rHHHiPGyNHREdGnPhRKM51MuHZ4jeneFGdbXnrpOZxtIXq8TeVgZrMZRqcc1JvXDyj2Ui3ToihYLBYsF8tk5LrInVdfYb1ecbi3T/CBZt4yGo1QSrFcLvC2xShFoRVGq/5DYtuWV15+CSXpvLH7b1yXaPZQXrFqG7z3hK7kzP7+AUeLNR5hMhrhQ8DahuvXbqCVQqFYLtbMZsfUZcFIKopSMFoQFbl95yUEYVRVSOeFfPrzn+fg+jXe8+VfjrMtLgYm4wpCxGJTiRblQRVJqKiasG4cMYBIiSjBBU+MyYCt65r5HY9dNUgEYwrquqKe7FGN92i8Q7Rhb/+AldO0LtCsVvguZ26bEyqnBLPS/t3xdX7O9Bmu+MHxfch2f87Xyvd+s2rSJ4/p24oxolQaA5t7PhuomcxDz3/z3Lfw0d/4StRavf7BmUwm8w7jV9YFf/KX/gzSqIf+wdsVMUoHBt+gQOHGm9gvTs9SEpXThuPb0qOzFEI7t86pkjC8hgHQf6YYdwznN9PXs+tObvsUupe1DiWKspAuPDcASZCnFz8CUo3QLsfTd8JCpTapLIkxRDwRQ1VVlEVJ0SnrhhCSJy0kZdokauRpmgZrbRI9csmgsNZuXqmMiepCZDUikkrHxMBoVHXfYUBENsJFs9kcJTCZjHA+lY8pRKOi0JQt8+WCddMwLicYY6jrmrvzJc4l9dzU1oiqLBERnHUYYyjLEq1Tjm5EUqma0HmMVfK+ikoe0Hpco00qc0MMKKBtLcF7iF2IbOhyI5VC6RLaQBRQSnelgmL6PUZsm2qpaoFRXWGUIhAIUeEDqRasigSlaK2nsYH1coFtm+0YEDqjd9eD/1q1SXf3nzZIh17+4TDuQ3DPLEP0OirSw3Ofd3+eVbLm7byHM5nMO5+FK1GrbJBmHlzijZb3PHGbLytf5ryIgcyDSxs1aqkhV/q5KkZpQkTt2J27HpuBaNBJb+VZHse3cW27G7q764Xa1W85cdxm/R83Bu0bbHGTo3eWR4xNmymgtTdKF8slwRsOJzWIwvlODIdtOKZSisViwWQy4ebNm7g21QodVTWFKSiKAh8BiUynU6qyYFSXLJdLYgxUVYFrGlxX1sVay0svvcRkMklGrg8E71mv17S27YSOAsZoCl1QFgbvPYv5jNFoxP7eHk3TELxDa814VLO3t8d6tcQYxY3rB6xWK9q2TYrCollXa5r1iqPZnJsHU4qi3BjYq3UylqtqnBSHyxqIyUNap9/xDqUNMYIPHmJM4bxap1qjhUEXhhuTmyBwPLvHqKowSrNcelQfKh4iUVKOrhiFmJJASwC01kSVvp/SFDjnWK8WRB8olGJ/MiHGBh9XWA/iAku7JKiCoCJrG2msY3F8l6ZZprxO+oiBLunyjAcyQ29nz2lDbxBlMLjH+n3bnOreG797ztfzmp79QGcYEnz2ccPPEELIBmomk8lkHnje++TL/MJX/hzZIM087Fwpo/T16fNOh6bg1Vm4nsw97X/2PtU365bvz3dWOGYvEuN8TGVDjMZ3ZUm0rohB0TYBCQ3GaOqqoq5rys5zaK3lxRdfZFSPMNrQrhsmkwnj0YjZbIYPjhs3bhCcxdmWpvMQVkYlr6FEtFJQFEyn08252zZ5RxfzJePxmL3phNVqiWoUxhQs5jNCCIyqiqosKLRi3jbJMN5LdVYVcPP6dSKB9XKePJyTEQLUVUlVj3jhldvcO54lT2d3fUajEcoUjEc1WimadYt36RpqrdFdORzfGTzrxjKqa8qqYH58RCQyLQzL1YrVasn+dIo2GlMITQNeacaj8SaP2Lk1IYIqDQSBqEEMWivG4wlWumznCM55lssly/mMdn6MDp6qKpnu74Gp8D4ZsqIMog2FUoQotKsFzjfp+1eSnst0gkbI7kMSGTzIOMlZhmAfLrs9ZpirOhyHZ4/NTCaTyWQymUzm7eCKGaUDxZOz0944mRM3VNDdqe85PN9gy46I0HlNnGxxeF7Z3bYbgniiP1t90p0SF9tw5J0fO109LdJ0tpe2P0wNDdYAPkaC90nGqPOQJvXeXlE11SAtdIEgtOs1WuuNURkJ1KMR7SrSrlfJKxjp6oP2+bJxEHJbYkyBtZGkOgyFKTBGsV7NIWqiNjhrCTFSVgVG6+QR65RY+1qcIUBVVYTose2KojCURUEMHq00ylSM6mTUGmNQWiNKYYwhIBiju5BZtQlbLsoC7x3eGPAehCREJYJSmhB38ydDDLTWUkjEFGW3LaJ1UlcOPnTXJCkfqyhdyG4Kl46qU/oh4JxPYdI+4J3DOYsKHqUMZT3BRYOPsgkbRhRK0nflvSV26reyqZdyxsjdiBLx+hblcJzt/tmdehAqPHj7TrmjE+dJ3/lbMVS3nt7d+ruZTCaTyWQy7zzMl72b2fuuUYu/7K68o7giRqkgXd5lV/gRotlZMctGe/W0oEun/8LuEjupw3Zv7vyUSR21F0by0W/2v2ViGLw/rc6T3qzujMZtyQs5tdzuDJeYzNYdz5X0weXxhDGQPkcMA6M0eLCWybSmMJo7d5doAS3C4cEYrQwhwmq9Zr1eE2OkKksOD/YBwdqWu0dHzBZLjmZzxqMxk/GIUT3GrtesVivqMsn1B9egiwKtClbLJYiiKCqqeppKmzjwtWVUj1gtj1mtVl0I8Ij9vQPW1uNCBHEslyvuHh2hilTaZf/mdbyLLFpLVeq+eAhKFFqSuBEiFNrw1GPXmU4Me/u3UKYEXSLFEULAxcj+dMq1a9d57oUX8c7zyMF1mvWKVbGgLRcQk6dXRcFbh0hMarch1Wwtjebu7ZcRGTO6cQ0hHV+NC2xraZ1FTMoBWDSOySR5RxdLS2sty6MjSq0xSjE/XkOITEyNNQVea7xbYoPCUqFNhVKGVYgEDDEqnLN4t0YbR/QRHyBEvR3TXXjtcMycZcyF7c2xHaKbpx5bH76WuDFS+z3SvTcN0RPJDptmt0Zlb9Rv9nTt9sJF0O+PDO/PVNaJJAomXUTBxqjPZDKZTCaTeefw/F+s+f++5od53EwvuyvvKK6EUboJeN3xtAzKwEBXEkR28uheSxV015u06xLa5qCeb42enff22qvkofEYZdvONp/0tEjS5rNucgHPzwE8pYQqsjEy+ly9dBqP1rortaKBwGw+x2iNVum44H2Xx1mgtebg4ICqqhmPJiwXC5bLJYvFkmWXz1mWNVorggSCtzjrqOoRSpKgT9M0tNbz6I1bhOCYzx1G7+Fcyb07r2Cdx4dIMjIjyhQY3aK0UJapREvTrCEqYkh1PlVndIUQcd6lmqFEQogphxTwIVLqgv1rN3j17h2a1tG2lsVivrlERWGSR7Y7X1VWqR5pWSbjz3vqusZondrzAQ+bv3tlWBGFtR5rLW3bppI7ohnVUyRG1stl+q5UKl/Qto7WB5bLBdF5ls4mwabCEEKBMQVam05sKaRyPF7hbPKoeu/OGI90+cbJY/uWFGo3Y6bzjnJyPPYNDd4ipyMReiGkszhP3Gj3fjibzV2b1XczmQeW8I1fzTPfPOK7b/y9y+5KJpPJvK3s1U02SN8CV8Io7dld+PbCKLvHnPTGAJscv90D6TyWvaEnO6Vj3qz67VlKoX3rp861Y5AODcoT79+om/ZvDAztzX7bQElpE3qrlNp85j6XMBkZEcF35UYKilITguf4eJFyOI2hKAqa9Zp7dxvqesRoNOaJJ55kMp4ymUx5+umnWc4XHB0fsVosWLcN+13ZFzHCcmFpbcv+/iFKa6zzzBcrrAt8+bvfQ4wBa9eUZU0MjldeegGRFutc8vaJQuuUY1oUSRFXacVyMcfoisKUeOuJSiiNIsSAdY7pdEoIgfV6zXg8QYqSV28vMXslN2/e4pnnnmM+X7Jer7u81jkHh9cpyxIf/DbcuKowRjMejZjPU33V8XiyUeX1zhOdpyiSwe69x6ikGtw2LW2TRJ68dWhTcP3aTdYxsJjNiMqglCBR0TQt7aphuZzjmga7WDAdaerSEKmTqJLWWBsIESbViNB6/LrFOYtzdjPeT4pppe9Znztet0PxxIOcYez69h3njPzNCTs7dvBAZTC+U/9OxAJz9j22vSdO39uZTObh4fl/e8xv/ad/5bK7kclkMpeGjwF7zlruYeTKGKWnw/56UaN+465a8jA3slsyd3U8e3XPreEXYzLYTtYy7SMZ37h5mryvJ8MR9UChdGOMEk4s2s9oZePM7QJ9uxDkdCnUZnt/hJZdYZoIXZ6jYTQaEYJDjOGJRx+hKM3GQ+gcFEXB4eEh49GI27dvUxQFtx65SVkmgSJrLcvlAuc8j9y6ibOWZ599nro0TCeHWOdBhIO9CaPxCKLnzu07hBAxZUld10yMYb5cAAFUUgO27RqUwQeYLZa4NpWOeeSRR6iLEplMuXfvLtY6UML+3j7FRLh3fAxAPRpxeHjAaFRz9/iIuqq49dijHB3PGTWWx259KQFDs1ozHU8I3tGs10jZKQm7lqAV9d4+odA4p1jOj2nbgG0bjDHs7+9jrcX3olEqGfqTSarBalvPeGQotObenVcpi4Jr124wP7pHCJH1eg2VYTSqsIEUaoumrhSFVHi/plBQK4Vvj1muGh69eRNtimTwFhVRFbRe0VjLyjYcz45pm+Ugh1edNjZ3cp1Ph80Ot58UOEqbuxjwE9nV/T20M84HR8XufJtt3T0YOVtZ96TXtPc8n/Ec6a17fzOZTCaTyWTeIfgY+ObP/Ad88cUbOV2p40oZpWeFrQ6Fg3b2DBe95510J8/0hHdVtmbia62BzwrfPRXGOAg0jn0OHruL8LPbOCv8sQ8rjm8611VEUt5jaSjKAmM0q3WDkISD+pdSCqM1ZVl24b2wXC5pdEtZWKZ7E0xhCKEz6JVGVBIPUlqjJOXmhhgJwXdtp/Zb23QGeMR7j/OeqqoQUV3+Y6oLatsWCGglSTAohE7gBwqjiJ1nM4TkYlY69VOUoqwqiqLBR9jf36d1kdkyqQwXxmDVwDgKgRB8CoWNycNsCkPs6q4OH2REIs45RAtohdYFSqc8R9199v4hQ1EUKKXw0eNCQIW4CWmNXX5wVCAS0VqjKNCiWbk53kfKeoxSGhsCymjQBU4UqKQS7EMSROqv7emQATkdUnvWPXRCE0m2MbvEEDshrNcZV4NI9z4qoTcgBx3ite7Rs7f1ndvcPa/dkUwm89AwD2v+RVvz8nLvsruSyWQybzuByDOvXIOXq8vuypXhyhilb4WTi95e9CXGJC2kfk8KRme1dXrRHMLAiKTP+Ut5hW/knCeP2uaG9qJJw7Y8vSBS7OKBlQjeO1arFdeu7VFVBXbdpnBTXbBerjCF4datW5QmhZYeHh5CjF2Y6xznPPP5Aq0NVVnz2LseY2864Yknn0riQMsl127coK5KYnQsVguaZtUZm6CNYdW0LNdLlE6lTYwxgGB0yeNPPIHq+rpazGiaFS+/9DxlWVCPKqbTMQCmKjnc32N/OsW2Dc4HimqEVskYvHnzJsaYVPsUj1KRstRok8xgJZ6I42B/ig8R7x0xxkH5m5LRqOJdj78LiNy78yp3795jPl/wxBNP4rzj1Tv3qCpDXRbcODygLEvKqqQsK5QoRqMU5uucw4aIC0BUeOvxYY33ghJNUY9p/ZKmXVGYElNWjLRGhYa2Ecb719I4XS0oxyOUqZjbiklZM9nf5+joFdarlBvcS2UNjU6l1NYIPuM+OLl96GlNHtDO0ymnjcl+bO5u4IQRevK4bbTCqTF+yuoVBkpJO4300Q+9YnQmk3k4+WfrPf7Mz/8pxOXIiUwmk3kYuJpGaXLHnN7eeT7PCg3ckQ2KcUet9yxPUG/Uvalu9YZiPJmjt/U2xdit33dCiXc/z/a9SZtXidr1RMlwIT9wdcXToZEupNqkMcZUDzSWMCnxztNimc9XaK0oyyP2phPqqqIoCmIIeGeZTqcURcmtW4+ilEYrw2hcp3qePhnBxhQEH7HW4W2D98njqEWIMdA0TReSKSxXKwpjGI1qXPB452iPGrQRylJzPLvDer3COQd4YvSMxmMQYbVYYAQkBqqqokQQXbJu1qzbNY899mjy1GrNaFRThWSUti6iVKRpVqyWC+i8kFprlEre46LSFGWB1orVeol3lqPje4SuXqhzDgQm0ylVaZL6b1f2xntP29pN2Z0YIt4H6tGEqDTF5ACnKqxUrBYNznnWsxkSYjKirSOEiA2eoigp9BSlDKIiNRWiFWjNtNqjsS3L9eKEGJaczkfuxYlk12N6VhjvqRzsvs7pyRD5wftORgOEEHa2R9lu23jA4+lznOXNFRnEzMft54nD/ZlM5oFEP/IIT/+538f7/tAXXv9g/6byazKZTCbzDubKGKU7npk+z3KQq5k2qjPf04fM7izIGS63ZTdIcCAQdDandwxz5c4WSZLNOU/mrp7dJzpF4ZiM0I1V2hkefaHSYQhyZ58OF/u+C0NNRukaHT3EA5wLOG9ZrdYgYApDYVK9z5Rr6XC2ZTrdY39/n4P9AxBFDNC0a5xzuKaBmIxS5zwxBKxt0CoZIhpwLhmlpujDhdeEoqCqUl1Q6yyL2ZyiVIwnhuP5XZrVCqMqotUE5xlPJogIy8USFSMSPPsH11HG4KPmeL6kadY8+tijKK0QJYxGdQqjLRUBj6hI265ZrZZoZSjLqlPZFbTqaqmaJLC0Wi5pmhXHx0eM6jGjUU3wHmU0070pldEUJo21lJPrEdqN8ztGCD5SjSaooqKYHGClxEhJswoE75nNZ0yqiroscVbwPmBDoDQVRpcpHFpHKlXilCIqYTSd4OeRdtYS+hIsvYq0DESKNuPi/FzSs9gcqzYDqTvVUALs9BiPMab6qTHirU3jWKWwZpEuHDoKPiZvfoygB214n7ahFFprtFb41kMEbfRGiKn1bfeQJhulmcwDy81D/v5/9MN8VTm67J5kMplM5gpxZYzS0wyfkPYL4NOeQujDGtnd171ddh607tYu3cq3wFmG6JDdNnvjOC3kPSHVWe0MUhFBiTrR30Hhja5thaBOGrC9rbCxgM7vT4ikupbKIMZQFyWmLDi2kUoCZQGP3Lq5MTKU0gjCer1GiTAajVI1Ve8YlRVN03J0NGPR1TLdm45TLU+B5198kRADt27eoChKqlLzwvPPpnIqVc3e/jUmkwnHd+/gvWU1nyUBHOdomjnOCtEaxkXFWBf4xoEWlI4sZveIUaEwIAaP4Wg2oygKDvYPeOTaASKHSAzMZsfM5ksee+IJ9g4PCEHR2obFbE5V10ymE+7du8f+/gHT6V4qWeMjy8UMo5JRWuiUDzse1Txy4zqHBwc46/DeY51DnMM1nt957mUmkwmPPvZ4cugpQQmp7mpVM28tTdvQmgaMIurkXfbeY6Jg1y1u3bJcHmFE2KtrqklFXSqaxd0Ufl1o2ggemPtXWS0XrGZH4CyKgI0ekS4UXaVxIwIEBVFQqh9jEGOgryc6VHg+pR7dRQmImE1YesR0g81vwsJjTLm+Ac8f/ubv4N1f8W/wkb/811gt5oxHFf/Od32IL/uKr0LmrxJNDaNDfuYn/w737r7K93zP93P3C5/jmU98jN/+zNOsA9Tv/wAf+Lqv5/e//wP8nb/8I4yqiv/we78XUULTrPi///e/xOzo7qk82Ewmk8lkMpnMg82VMkpPi6DscnKtOqzdKIOQ32Hka2+Y9uIsQ+dr3PzbyRXteJ3O6+U2lHInZJh4QlBm9+fJjyVd/096bzeHDQzyk57d0yHLvfKpAoTWObQBE1N+Z+wEiWIM+BDQ2qCVoHWSmY0hYltL26b6m86mUFalkhcrxJCMGNLxIUas9bTWAxFdFIio5PeNKbTVuRTumr4WD0EgJC+ZJHsq5aNqIZXu0alup9KE0HmCQwoZrqpUyiaGmGqIOp8eL4giisK5wHK12oSSemfTy7tubKTv13mHdxEzqlGiqEep9moMgeBdCrkmpnZCQHXiTLLx+nUPOWLoyrXE7voAIWV+hhCSaFNI1zoGj3e28/Cmz2sKTbDdlyyCShVZab3H2ZZ2vSIG14+qzZjd1rKVwdA7Hc7bj5Gd43e2bXOZ+wc6w9Gcwmu3YboRaFtLs264fuMGq6rqclEVIQi3Hn8CXU2I9SGmrEE0t971FPb2S0jreOzJJwn1mPq97+PGo09Qj/aJYjDViFtPfAlKwXq1QHdiVpto9dfx/GYymQeTj64UH5195eD/g5lMJpN50LlSRulboS+3MqxvOti78+sb+x/c7z10cGuQDozJzqCRoRH8BtxBw1DKk6GaO5mp3XHeOxaLJUoqClXho0METKFwrqVpFLdu3YJIKp0imhCFl2+/msR7rMVHNkq7tm1o1itu3LiB1gqthNVqSbNaEGKkLEume/u0zrO+d8RsviR4C8ExqQuMFoyA0UJpNCqmPNIYulqqRcl4eoAuSkQMy1XDctUwObgGwJ07x+wfTJlMNEF5BGE6maJE4Z1HmZKVdbz4ym3WqzXBeyKBpl1zfHyE1ilceW9vj7ZZ067XTMYj6rpkMh6zWi556aVjcB5tDKPJBBcCQYTHn3yKqjSUpYEQiJ1a8Hq95Gi1ZnLtJkVZ40RjfRJUstbjXCBYh7MN3rcQPdooCgPaCEoryroGJUhRUOoJUQpmTuFby/z4CGtbYvRdeRo5ZWAqJRDl3PHRl3TpxYJ6AaKhYfoGRzOI4tc++sv8y1/55/yxP/JNWGf53Wd/l0/+s3/Kp3/94/zH//kPMCo1iMWv5vjlHLTi6M49vvDpz/FdH/5BHn/f+2Byk9/93Bf4V7/6a9jlErW/B8awqcU7jE7OBmkm81Bio+dPf+z78C+ML7srmUwmk7mPXCmjtM+TPEvo5GwP6XYx3ocbbrfvGnDSLXrlhNEZT7WVyqAMz7+zd6eN3T5t+nWGiMzWuSVbxdN4Xvbp6c96bn/C1kO7Ve7tPqeAdz6FrBaGsixTWZhOSbYsCpJn1aJVgTYFZVWzalt8CMzmsyRaNBkTXFKyNVVBURgUoySSVBaMxxMWiwXOtuwfHEDwuHZNaJc0tqWuSozWVGWJFoFQYEhCQgK0zQrlLEU5wmhhMq4hBlCKejRGlMH6gIrJu1tWBiHlNxo9pigqDg6vsVzOsU1DWaZyLc45tC4217AwBWasuvIyEe8cdAJNNiRvbggeXVYUukjiRM6jnUUBSlJ+rQCyyesFEZUUgpVhtVjSrFbgWmyzxtuG8aSmNBqjBWIgBEdRFSmHVymCKHyExWyGbdcYrVECXuJmCJ00Sjd512zvm9caO7vbToTzDsdY2ASZb9sJqd8uNnz6U79JCJ7jxT2aJiJi+Mc/+RF0VRK1Zv3Cv6ZYLPnHP/5jvPz8MxxVnn/+0V9k8hsfJ5ia+b1jZnfvwfoOs5dX/IOf+DFUhOAs68UC2BrQWfAok3lIifnez2QyDy4fmd3gbz/3QexRdWYtgoeVK2WUwvkL7G7nueGuuwbnG/Sy9Oc7Fba7qyR6sk+vawDEJF60E0K5+TcZpOd5Sc8yuPv2h+VA+mbi4H3SCc8MwztDCCgtqYZnJ3LUK9MWRUnTrLHOI50Q0mg0xsZIsC2r9Ro9GVPVExazGRICIiXGFBRaMRqNMMZQmAIi+BA4nEwhBuxaM2uXOGupCoPRhqIwaAFiQMcUFhxiwLUNopIBqZRBGUPojHpTliAK72OXQ5lUdIkB7xwRoSgq9vYPefG5Z3C2ReuUB9vXUO0xhUFLgVYKQQjeIYBWCkvscjIjRVFgiopgm07oyGKU6mq1KsRohJLY5zJ3OcRaNE3TsF6tKCTgrcXblkKNKbTuxH8CMQjGdJ+LFP4bQqRZrfDWpuP6cPRBvPlJNed+vJ+lcrsZS+d4Us8atyfH+PYBTPonOMfvfOG3iXiicpu81k/8kxeICoKOGA86RD7x0Z+nMbAqhU//5seRIPg4uBcksrLHfOyjP4+OKTTcq23brzkPZDKZTCaTybxD+ei9r+Dp33gqG6QnuBJGaVrz/h4WoH1criTRlm4VzdsRitvzZvonsn1tvFkpI3OzrTdNhzmjb+zcu59JSHmjZZlqcBotqOiS0BJQViVVWbC3N6U0BRD53Oc+x3Qy5Uue+hKWqwZrLfWNKaYoKcoKFguUKA5v3iQGz3K5JMaI1prJZEL0jugtjW2ZL5esVkuKsqSsa3wELYqyrtjb28OVimYxQ3TAGEW7aoneM65qXKfOmww+RfQN9+69yvF8wWPv+hKUKTlerphO9hiPxxRVCUTmsxm6qimqwN61kv3Dimo05sXnvshsdo87R3cYjSbs79dd+GsysCbjKft7U9pmjZLAqNRIrCDCUitMUbJ3eIgVjUdRlQUxWrxbQQzE6GlblWquqt7LCc57Wt/QuLYz9g00S4yka2ZEKLViNDadxz7iXEBphSoKlrMVTRvZn+7h2zW353OCdzvfubBbKqXPRz75EGPXmIw7x++Omt16pjuGa9zWC/UhYumzlgOoQEAIlCgCIrA0BToKxitsFKJEgnZ43YBa44JBxKDdQboLouCLFan6Kjj65zjJGNVabxSlM5lMJpPJZDIPPlfCKO05vYge/E1vym2OZqDHMhBB6pJH4663cXvq3cU3IidEis5Q8n1jvd/2QnqvVrcrxFM5cxvxmmE7O32Rnc/X/z3sV4z9K6muGq1SKZOwFeAZ1RVFoWlbi1Ya0V39TSLWtp03MW7FfkOqm6qVSaJDMZkOIoIo6UqVhK4siAbxtNZiCoMSkBhwztGu52AboveE4CCmuqaKFJllTAkk0SRtCkQrlDZUtWccwRiDiCL5EtPnbBuLUtIp6ga8dRA82hRUkxGj8ZRRPUYf3yV6R9usKHRJNKa7zgHvXSf65GmiQ2JIgkqd17VpGrwqCEqn0iTB4b3D1DXaGESbzVj0MeJDTOVzvOAsEByKiDEajyZKCp/WJoVQxxC6OqceRGFEdSJRHmvXWNvgnO2uMJ1G8+mc0oGC1874S8q82zE2GJXdUSce1nTGba/a2z8kid13s3m+070zeee34zkmBzYB0ljpTt2NKlTUQCeCJb5Tp1YpD/rU/RMHwlSZTOZBw37T1/H8V1fsKX/m/k+0a/7J8r24xryNj5QzmavNC7M9/sbRu/j3J5/jcTM997jqfUccfe8Huf7/fhZ/9+597GEmc3+4UkbplrRkHUQuJsRtDLb+lYzLbVAsdHmigxVvn1PaL4RVaiKhBiGKOz9fO1x3yFbYKAm2iBoYEZuPEDdZpptX5zUV1dnHO0t1TYwDw3Zztt1+BRcIXZio0VPKQkNMeas+RPYO9oghcOfuXa5dU0wnBQfXD9FKWKxn0BmzSfjUY21DoQqMGKJPIaJa62RsKGHdrJJHi0g5mhBFEUJAokeLR4KlWcx48flnGBdCoQX8GjGKEohGQ1RU5RilHVEXlHWFMgZjSqYH10EE13isD/ioMCq1cffuMXVdcePmIU2zxq3XRLtElVP0dMzh4U3WszXz49s0bcvRnVcodUVhUthw26yZJcsRgmPuFrjWErxPeclaM1uuKCd7FGXNOngEj1Ke6fSQajSmLDUhOKxtWbuAixYra1wQnBOCW6Nw7E0qmtZjraMoDWVZUNc1bp2MThtS/dhSTTFliQ6We7dfYDa/hw1t52kXJOrT90EauCAKpHtIEPpQcUGGZWFCoLcr+7sqdgEjQeKgHG5SDyamhxkxgg9pjCm2D0DCZvgF+tRt6c7uJG7Uervga5QrNud3er0Tjr4zrAf04bvZOM1kHizaP3eXT/6BnwbOXnj/6Mt/lF/8lT+YDdLMQ8Xitw/4C1/4Tva//e/yob3zjc1P/qH/ixe+bs6f/Ox/Bh/LRmnmweNKGaW7i9B4wiA9eezgyM3C+qQ39fWI23IYojjL9jxP2GjY51NqpjESNx6orSk59Miezpnb9lyUsHFc7eTJns4ZTLmiJWWZch+FZGT2ZU5sm0JKp9MpwQfm8znGGIzWSIxMx1OKokwhumFJCMJkskdZlKjOwFAitG3yeDYrx7iuGdUVy8WK4D17e/sUOvV5OV9g25a6qpjUhlIL0Sm0UqzXa0KwiEr1NTUKQ8pvFVF473E24iPgfCoNQ2S1WhCWC+rRBJEUdlpVNQjM5zOKGKmKkslkzLVrh7z0Uo0PgdZafPCb2qHEVHfT6OR/LIqK6FMJmNFoBEgyhJ1HtGdcFhhdUqiIbx0rv6A1Ch8c1jc0rmBtA8/ffpZ6tMdovE/brlFd3mhdGcajPfb2J1RVQYweUYIxhuA9bduyeOUV2lhgffpcSqvuu03fvXTez1MGWu+ljKn27llh3cnzvruxM1sHbSTLUqWzdKV63kBIeRdl0I/D/slQrwodhU3t3qFw0fmG5tsbbp/JZK4eKtd4yWROUX/pjO/7/b/GHx49w3kPbDKZh4EraZTGwb8XTV9rsm//tRR3z+O8dfbOMvvEKc5TGe69XW+ElE+qupdJOYCeLozWEyXivEdrTVVVqbxL47r3RrxXmKKgqiqOj2dY67GtZzSapNqcm/DiJBrknMO1K0qjgYq2tQDUVY1ERwzJ0ArOUxZFehkhKk8MEdd5KXUnxtQbpkopUIJ3AecC1kfUxpAh1e50nroeb651Cu8VmqYlmBbtLGVZMB6PkjpwozbfZwihM4ySYa9FgwKtTKrFiqMoSkKMtK7ZHK+1xhhFqYXgPdZ5rJPOKG1pfWC5drzyym32DyKiKpx3GAnEmOquJg9phSkUofcAKpWEf6xjvlyBrgnogVjV0GjcGpFnjrEYERkIAw2MxdNDb+h534b7btWqzx6TfTvnjdm+j3F450aI0j30OUNoafh7b7RmMplMJvOw8eThEf/djafJBmnmYUeugpiIiLwCLIDbl9yVm7kPl95+7kPuw5AvjTE+contv63kuS734Yq1n/twdfqQ57qL4bK/19yHq9OHy24/9yFx7lx3JYxSABH59Rjj1+c+XG4fLrv93Ifchwedq3BNcx+uRh8uu/3ch6vVhweNq3BNcx9yH65K+7kPr08ukZPJZDKZTCaTyWQymUsjG6WZTCaTyWQymUwmk7k0rpJR+jcuuwPkPlyF9iH3oSf34cHkKlzT3IfEZffhstuH3Ieeq9CHB42rcE1zHxK5D5ffPuQ+vCZXJqc0k8lkMplMJpPJZDIPH1fJU5rJZDKZTCaTyWQymYeMbJRmMplMJpPJZDKZTObSuBJGqYh8q4h8VkQ+LyJ//j6095SI/LKIfFpE/pWI/Nlu+3UR+Yci8nT389p96IsWkX8pIj/X/f0eEfnV7lr8XREpL7j9QxH5KRH5LRH5jIh8w/2+DiLyX3ffw6dE5MdFpL7o6yAi/6eIvCwinxpsO/NzS+IvdX35hIh87QX24X/uvotPiMjPiMjhYN+Huz58VkS+5SLaH+z7QRGJInKz+/tCrsHDRp7r8lyX57rNtvs2153Xh8G+PN+9zeS5Ls91ea7bbMtz3Rvk0o1SEdHAjwLfBrwf+G4Ref8FN+uAH4wxvh/4IPBfdG3+eeCXYozvBX6p+/ui+bPAZwZ//wXgL8YYfx9wF/iBC27/R4CfjzF+BfAHu77ct+sgIk8A/yXw9THGDwAa+BAXfx3+FvCtJ7ad97m/DXhv9/rTwF+9wD78Q+ADMcY/AHwO+DBANz4/BHxV956/0t07b3f7iMhTwDcDvzvYfFHX4KEhz3V5riPPdUPu51x3Xh/yfHcB5Lkuz3XkuW5InuveKDHGS30B3wD8wuDvDwMfvs99+H+Afw/4LPB4t+1x4LMX3O6TpJvkjwE/BwhwGzBnXZsLaP8A+AKd4NVg+327DsATwDPAdcB01+Fb7sd1AN4NfOr1Pjfw14HvPuu4t7sPJ/Z9F/CR7ved+wL4BeAbLqJ94KdI/yP7InDzoq/Bw/LKc12e6/Jcd3lz3Xl9yPPd2//Kc12e6/Jcl+e6t/K6dE8p28Hb82y37b4gIu8Gvgb4VeDRGOML3a4XgUcvuPn/DfhvgdD9fQO4F2N03d8XfS3eA7wC/M0u1OT/EJEJ9/E6xBifA/4X0pObF4Aj4OPc3+vQc97nvqwx+qeAf3A/+yAifxx4Lsb4myd2Xep9+oCQ57o81+W57mzu+1wHeb67QPJcl+e6PNedTZ7rXoOrYJReGiIyBf4e8F/FGI+H+2J6ZHBh9XJE5DuAl2OMH7+oNt4ABvha4K/GGL8GWHAipOM+XIdrwB8nTaTvAiacEXZwv7noz/16iMgPkcKRPnIf2xwD/z3wP9yvNjP3hzzX5bnuPB7Gua5rN893DyB5rstz3Xnkue7qz3VXwSh9Dnhq8PeT3bYLRUQK0sT1kRjjT3ebXxKRx7v9jwMvX2AX/i3gO0Xki8BPkEI9fgQ4FBHTHXPR1+JZ4NkY4692f/8UaTK7n9fhm4AvxBhfiTFa4KdJ1+Z+Xoee8z73fR2jIvKfAN8BfE83id6vPnw56X8iv9mNyyeBfyEij92n9h908lyX57o81w24xLkO8nx3keS5Ls91ea4bkOe6N8ZVMEo/BrxXkipXSUr6/dmLbFBEBPgx4DMxxh8e7PpZ4Pu737+flJNwIcQYPxxjfDLG+G7SZ/5HMcbvAX4Z+BP3qQ8vAs+IyPu6Tf8u8Gnu43UghXd8UETG3ffS9+G+XYcB533unwW+r1Mp+yBwNAgHeVsRkW8lhf58Z4xxeaJvHxKRSkTeQ0pK/7W3s+0Y4ydjjLdijO/uxuWzwNd24+S+XYMHmDzX5bkuz3UdlznXQZ7vLpg81+W5Ls91HXmue3OdvfQX8O0kRap/DfzQfWjvG0ku/E8Av9G9vp0U+/9LwNPALwLX79Pn/yPAz3W/fxlpUH4e+EmguuC2vxr49e5a/H3g2v2+DsD/CPwW8CngbwPVRV8H4MdJuQ6WdIP+wHmfmyRU8KPd+PwkSVHuovrweVJ8fz8u/9rg+B/q+vBZ4Nsuov0T+7/INhn+Qq7Bw/bKc12e6/Jcd//nuvP6cGJ/nu/e3nGX57o81+W5Ls91b+olXacymUwmk8lkMplMJpO571yF8N1MJpPJZDKZTCaTyTykZKM0k8lkMplMJpPJZDKXRjZKM5lMJpPJZDKZTCZzaWSjNJPJZDKZTCaTyWQyl0Y2SjOZTCaTyWQymUwmc2lkozSTyWQymUwmk8lkMpdGNkozmUwmk8lkMplMJnNp/P8Aum57f9xi2wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = val_gen[0]\n",
    "val_preds = model.predict(tf.constant(x))\n",
    "plot_results(x, y, val_preds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_func_from_saved_model(saved_model_dir):\n",
    "    saved_model_loaded = tf.saved_model.load(\n",
    "        saved_model_dir, tags=[tag_constants.SERVING])\n",
    "    graph_func = saved_model_loaded.signatures[\n",
    "        signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]\n",
    "    return graph_func, saved_model_loaded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_and_benchmark_throughput(batched_input, model, N_warmup_run=50, N_run=500,\n",
    "                                     result_key='predictions'):\n",
    "    elapsed_time = []\n",
    "    all_preds = []\n",
    "    batch_size = batched_input.shape[0]\n",
    "    elapsed_time = np.zeros(N_run)\n",
    "    for i in range(N_warmup_run):                                             \n",
    "        preds = model(batched_input)\n",
    "    \n",
    "    tmp = 0\n",
    "    for i in range(N_run):\n",
    "        start_time = time.time()\n",
    "        preds = model(batched_input)\n",
    "        # Force device synchronization with .numpy()\n",
    "        tmp += preds[result_key][0,0].numpy() \n",
    "        end_time = time.time()\n",
    "        elapsed_time[i] = end_time - start_time\n",
    "        all_preds.append(preds)\n",
    "\n",
    "        if i >= 50 and i % 50 == 0:\n",
    "            print('Steps {}-{} average: {:4.1f}ms'.format(i-50, i, (elapsed_time[i-50:i].mean()) * 1000))\n",
    "            \n",
    "    print('Latency {:4.1f}+/-{:4.1f} ms'.format(elapsed_time.mean(), elapsed_time.std()))\n",
    "    print('Throughput: {:.0f} images/s'.format(N_run * batch_size / elapsed_time.sum()))\n",
    "    return all_preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "output shape (4, 160, 160, 3)\n",
      "Steps 0-50 average:  5.1ms\n",
      "Steps 50-100 average:  5.2ms\n",
      "Steps 100-150 average:  5.1ms\n",
      "Steps 150-200 average:  5.2ms\n",
      "Steps 200-250 average:  5.2ms\n",
      "Steps 250-300 average:  5.3ms\n",
      "Steps 300-350 average:  5.2ms\n",
      "Steps 350-400 average:  5.2ms\n",
      "Steps 400-450 average:  5.2ms\n",
      "Latency  0.0+/- 0.0 ms\n",
      "Throughput: 773 images/s\n"
     ]
    }
   ],
   "source": [
    "func, _ = get_func_from_saved_model('unet_pets_saved_model')\n",
    "\n",
    "output = func(tf.constant(x))\n",
    "result_key = list(output.keys())[0]\n",
    "output = output[result_key]\n",
    "\n",
    "print('output shape', output.shape)\n",
    "\n",
    "res = predict_and_benchmark_throughput(tf.constant(x), func, result_key=result_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now prepare input data with different resolution and run inference using that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_size = (200, 200)\n",
    "batch_size = 4\n",
    "val_200 = OxfordPets(batch_size, img_size, val_inp_paths, val_target_paths)\n",
    "x, y = val_200[0]\n",
    "preds_200 = func(tf.constant(x))[result_key]\n",
    "plot_results(x, y, preds_200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have seen so far that a fully convolutional TF model can be used to infer images with different input sizes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert the model with TF-TRT\n",
    "In dynamic shape mode we will have a single engine that can handle the input shapes seen during build mode. We select profile strategy `'Range'`, and we need to define the range of input shapes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def trt_convert(input_path, output_path, input_shapes, dynamic_shape=False, prof_strategy='Range'):\n",
    "    conv_params=trt.TrtConversionParams(\n",
    "        precision_mode='FP16', minimum_segment_size=30,\n",
    "        max_workspace_size_bytes=1<<30, maximum_cached_engines=1)\n",
    "    converter = trt.TrtGraphConverterV2(\n",
    "        input_saved_model_dir=input_path, conversion_params=conv_params,\n",
    "        use_dynamic_shape=dynamic_shape, \n",
    "        dynamic_shape_profile_strategy=prof_strategy)\n",
    "    \n",
    "\n",
    "    converter.convert()\n",
    "    def input_fn():\n",
    "        for shapes in input_shapes:\n",
    "            # return a list of input tensors\n",
    "            yield [np.ones(shape=x).astype(np.float32) for x in shapes]\n",
    "    converter.build(input_fn)\n",
    "    converter.save(output_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Linked TensorRT version: (7, 2, 2)\n",
      "INFO:tensorflow:Loaded TensorRT version: (7, 2, 2)\n",
      "INFO:tensorflow:Assets written to: unet_pets_trt/assets\n"
     ]
    }
   ],
   "source": [
    "input_shapes = [[(4,160,160,3)], [(4,200,200,3)]]\n",
    "\n",
    "trt_convert(input_path=\"unet_pets_saved_model\", output_path=\"unet_pets_trt\",\n",
    "            input_shapes=input_shapes, dynamic_shape=True, prof_strategy='Range')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load converted model and run inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "trt_func, _ = get_func_from_saved_model('unet_pets_trt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = val_gen[0]\n",
    "\n",
    "trt_output = trt_func(tf.constant(x))[result_key]\n",
    "\n",
    "plot_results(x, y, trt_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Steps 0-50 average:  3.9ms\n",
      "Steps 50-100 average:  3.9ms\n",
      "Steps 100-150 average:  3.9ms\n",
      "Steps 150-200 average:  4.0ms\n",
      "Steps 200-250 average:  3.9ms\n",
      "Steps 250-300 average:  4.0ms\n",
      "Steps 300-350 average:  3.9ms\n",
      "Steps 350-400 average:  4.0ms\n",
      "Steps 400-450 average:  4.0ms\n",
      "Latency  0.0+/- 0.0 ms\n",
      "Throughput: 1018 images/s\n"
     ]
    }
   ],
   "source": [
    "x, y = val_gen[10]\n",
    "res = predict_and_benchmark_throughput(tf.constant(x), trt_func, result_key=result_key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predict with different image size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Steps 0-50 average:  4.3ms\n",
      "Steps 50-100 average:  4.3ms\n",
      "Steps 100-150 average:  4.3ms\n",
      "Steps 150-200 average:  4.3ms\n",
      "Steps 200-250 average:  4.3ms\n",
      "Steps 250-300 average:  4.4ms\n",
      "Steps 300-350 average:  4.4ms\n",
      "Steps 350-400 average:  4.4ms\n",
      "Steps 400-450 average:  4.4ms\n",
      "Latency  0.0+/- 0.0 ms\n",
      "Throughput: 916 images/s\n"
     ]
    }
   ],
   "source": [
    "x, y = val_200[10]\n",
    "res = predict_and_benchmark_throughput(tf.constant(x), trt_func, result_key=result_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
